1079 lines
224 KiB
Plaintext
1079 lines
224 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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||
"id": "be5b96b8",
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"metadata": {},
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"source": [
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"# OpenIE en castellano — spaCy ES + reglas de dependencia\n",
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"\n",
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"**Paradigma:** schema-less. El predicado es **el verbo del propio texto**, no de un vocabulario fijo.\n",
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"\n",
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"Ejemplo del dilema que resuelve esto:\n",
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"- Texto: `\"Enmanuel quiere a Ashlly\"`\n",
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"- GLiNER2 schema-driven (notebook 08): te emite `loves, knows, kissed, hugged, founded_by, owns...` — fuerza relaciones del schema\n",
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"- spaCy ES dep-rules: `(Enmanuel, querer, Ashlly)` — el verbo `querer` viene del texto\n",
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"\n",
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"## Por que spaCy ES nativo y NO 'translate + triplet-extract EN'\n",
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"\n",
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"| | spaCy ES nativo | Translate + triplet-extract EN |\n",
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"|---|---|---|\n",
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"| Velocidad | ~5ms / frase | ~500ms-1s / frase (MarianMT + extract) |\n",
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"| Predicado | Verbo original (`querer`, `abrazar`) | Verbo en EN (`loves`, `hugs`) — perdida del original |\n",
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"| Riesgo nombres propios | Cero | Traduccion puede romperlos (Enmanuel → Emmanuel) |\n",
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"| RAM extra | 50MB (es_core_news_md) | 300MB extra (MarianMT) |\n",
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"| Schema-less de verdad | SI | SI |\n",
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"| Maturity | Reglas hay que escribirlas | triplet-extract maduro pero EN-only |"
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]
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},
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{
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"cell_type": "markdown",
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"id": "19fba6c5",
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"metadata": {},
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"source": [
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"## 1. Setup"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "65118f52",
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||
"metadata": {
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||
"execution": {
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||
"iopub.execute_input": "2026-05-04T20:39:39.879993Z",
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||
"iopub.status.busy": "2026-05-04T20:39:39.879695Z",
|
||
"iopub.status.idle": "2026-05-04T20:39:42.801715Z",
|
||
"shell.execute_reply": "2026-05-04T20:39:42.800771Z"
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||
}
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||
},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"spaCy es_core_news_md ready in 0.81s (6 pipes)\n"
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]
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}
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],
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"source": [
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"import warnings; warnings.filterwarnings('ignore')\n",
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"import sys, json, time\n",
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"from pathlib import Path\n",
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"_pf = '/home/lucas/fn_registry/python/functions'\n",
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"sys.path = [p for p in sys.path if not p.startswith(_pf + '/')]\n",
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"if _pf not in sys.path: sys.path.insert(0, _pf)\n",
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"import pandas as pd\n",
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"import networkx as nx\n",
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"import matplotlib.pyplot as plt\n",
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"from matplotlib.patches import Patch\n",
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"import spacy\n",
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"\n",
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"t0 = time.time()\n",
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"nlp = spacy.load('es_core_news_md')\n",
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"print(f'spaCy es_core_news_md ready in {time.time()-t0:.2f}s ({sum(1 for _ in nlp.pipeline)} pipes)')"
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]
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},
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{
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"cell_type": "markdown",
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"id": "bfec983b",
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"metadata": {},
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"source": [
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"## 2. Reglas de extraccion mejoradas\n",
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"\n",
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"Las reglas cubren los casos clave del castellano:\n",
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"\n",
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"1. **Sujeto + verbo + objeto directo** (`obj`)\n",
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"2. **\"a\" personal** (`obl:agent` o `obl` con prep `a` sobre persona) — `abrazo a Tomas`\n",
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"3. **Objeto preposicional** con `en` (location), `de` (origen), `con` (compañia), `por` (agente)\n",
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"4. **Copular** (`ser`, `estar`) — `Pablo es presidente`\n",
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"5. **Verbos pronominales** (`se firmo`)\n",
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"6. **Filtrar tripletas con sujeto/objeto vacio o solo determinantes**"
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]
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},
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{
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"cell_type": "code",
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||
"execution_count": 2,
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||
"id": "23af50fd",
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||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-05-04T20:39:42.804011Z",
|
||
"iopub.status.busy": "2026-05-04T20:39:42.803722Z",
|
||
"iopub.status.idle": "2026-05-04T20:39:42.810615Z",
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||
"shell.execute_reply": "2026-05-04T20:39:42.809742Z"
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||
}
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||
},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"extract_triples ready\n"
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]
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}
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],
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"source": [
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"STOPS = {'el', 'la', 'los', 'las', 'un', 'una', 'unos', 'unas',\n",
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" 'esto', 'eso', 'aquello', 'esta', 'este', 'estos', 'estas',\n",
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" 'que', 'quien', 'cual'}\n",
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"\n",
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"def clean_span(span_tokens):\n",
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" \"\"\"Devuelve el texto del span quitando determinantes/preps al inicio si hace falta.\"\"\"\n",
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" toks = list(span_tokens)\n",
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" # quitar preposiciones iniciales (a, en, de, con, por...)\n",
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" while toks and toks[0].pos_ == 'ADP':\n",
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" toks = toks[1:]\n",
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" return ' '.join(t.text for t in toks).strip()\n",
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"\n",
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"def is_meaningful(text):\n",
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" if not text or not text.strip(): return False\n",
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" if text.lower() in STOPS: return False\n",
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" return True\n",
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"\n",
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"def extract_triples(doc):\n",
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" triples = []\n",
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" for tok in doc:\n",
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" if tok.pos_ not in ('VERB', 'AUX'):\n",
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" continue\n",
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" verb_lemma = tok.lemma_\n",
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" verb_form = tok.text\n",
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"\n",
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" # SUJETO\n",
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" subjs = [c for c in tok.children if c.dep_ in ('nsubj', 'nsubj:pass', 'csubj')]\n",
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" if not subjs:\n",
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" continue\n",
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"\n",
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" # OBJETOS — directos + oblicuos + complementos clausulares\n",
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" objects = []\n",
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" for c in tok.children:\n",
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" if c.dep_ in ('obj', 'dobj', 'iobj', 'attr', 'xcomp', 'ccomp'):\n",
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" objects.append((c, c.dep_, None))\n",
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" elif c.dep_ in ('obl', 'obl:agent', 'nmod'):\n",
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" # buscar la preposicion para etiquetarla\n",
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" prep = None\n",
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" for cc in c.children:\n",
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" if cc.dep_ == 'case' and cc.pos_ == 'ADP':\n",
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" prep = cc.text.lower(); break\n",
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" objects.append((c, c.dep_, prep))\n",
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"\n",
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" # COPULAR — `Pablo es presidente`\n",
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" # En spaCy ES la copula suele aparecer como tok.dep_ == cop sobre el atributo\n",
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" # Ya manejado via attr/xcomp arriba\n",
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"\n",
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" for s in subjs:\n",
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" s_text = clean_span(s.subtree)\n",
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" if not is_meaningful(s_text): continue\n",
|
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" for o, dep, prep in objects:\n",
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" o_text = clean_span(o.subtree)\n",
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" if not is_meaningful(o_text): continue\n",
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" # Etiqueta de relacion: lemma del verbo + prep si la hay\n",
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" rel = verb_lemma\n",
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" if prep and dep != 'obl:agent' and prep != 'a':\n",
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" rel = f'{verb_lemma}_{prep}'\n",
|
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" # marca pasiva\n",
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" if any(c.dep_ == 'nsubj:pass' for c in tok.children):\n",
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" rel = f'{verb_lemma}[pass]'\n",
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" triples.append({\n",
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||
" 'subject': s_text,\n",
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" 'relation': rel,\n",
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" 'object': o_text,\n",
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" 'verb_form': verb_form,\n",
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" 'object_dep': dep,\n",
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" 'prep': prep,\n",
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" })\n",
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" return triples\n",
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"\n",
|
||
"print('extract_triples ready')"
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]
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||
},
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||
{
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||
"cell_type": "markdown",
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||
"id": "1ff9dc34",
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||
"metadata": {},
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||
"source": [
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||
"## 3. Corpus de prueba\n",
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"\n",
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"Variedad de casos: personal, familiar, corporativo, pasiva refleja, copulares, OSINT."
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]
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||
},
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||
{
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||
"cell_type": "code",
|
||
"execution_count": 3,
|
||
"id": "73e37466",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-05-04T20:39:42.812134Z",
|
||
"iopub.status.busy": "2026-05-04T20:39:42.811989Z",
|
||
"iopub.status.idle": "2026-05-04T20:39:42.814973Z",
|
||
"shell.execute_reply": "2026-05-04T20:39:42.814323Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
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||
"name": "stdout",
|
||
"output_type": "stream",
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||
"text": [
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||
"personal_amor → Enmanuel quiere a Ashlly desde hace anos.\n",
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"personal_familia → Maria abrazo a su hermano Tomas tras la reunion.\n",
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"personal_amistad → Sara llamo a su madre Lucia para contarle las noticias.\n",
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"corporate_short → Carlos Torres preside BBVA, con sede central en Bilbao.\n",
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"corporate_history → Pablo Isla presidio Inditex de 2011 a 2022 y ahora forma parte del consejo de Telefonica.\n",
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"pasiva_refleja → Se firmaron acuerdos entre Iberdrola y Endesa.\n",
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"copular → Pablo Isla es expresidente de Inditex y consejero de Telefonica.\n",
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"osint → El grupo APT-29 atribuido a Rusia ataco empresas energeticas espanolas.\n",
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"biografico → Amancio Ortega fundo Inditex en 1985 en Arteixo.\n",
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||
"evento → El acuerdo movilizara dos mil millones en cinco anos.\n"
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||
]
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||
}
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||
],
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||
"source": [
|
||
"CORPUS = {\n",
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||
" 'personal_amor': 'Enmanuel quiere a Ashlly desde hace anos.',\n",
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" 'personal_familia': 'Maria abrazo a su hermano Tomas tras la reunion.',\n",
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" 'personal_amistad': 'Sara llamo a su madre Lucia para contarle las noticias.',\n",
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||
" 'corporate_short': 'Carlos Torres preside BBVA, con sede central en Bilbao.',\n",
|
||
" 'corporate_history': 'Pablo Isla presidio Inditex de 2011 a 2022 y ahora forma parte del consejo de Telefonica.',\n",
|
||
" 'pasiva_refleja': 'Se firmaron acuerdos entre Iberdrola y Endesa.',\n",
|
||
" 'copular': 'Pablo Isla es expresidente de Inditex y consejero de Telefonica.',\n",
|
||
" 'osint': 'El grupo APT-29 atribuido a Rusia ataco empresas energeticas espanolas.',\n",
|
||
" 'biografico': 'Amancio Ortega fundo Inditex en 1985 en Arteixo.',\n",
|
||
" 'evento': 'El acuerdo movilizara dos mil millones en cinco anos.',\n",
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||
"}\n",
|
||
"for k, v in CORPUS.items():\n",
|
||
" print(f'{k:20s} → {v}')"
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||
]
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||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "943bf7ff",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 4. Ejecutar — un texto, ver tripletas y entidades NER"
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||
]
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||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 4,
|
||
"id": "0ac506bf",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-05-04T20:39:42.816877Z",
|
||
"iopub.status.busy": "2026-05-04T20:39:42.816733Z",
|
||
"iopub.status.idle": "2026-05-04T20:39:42.868924Z",
|
||
"shell.execute_reply": "2026-05-04T20:39:42.867968Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>corpus</th>\n",
|
||
" <th>time_ms</th>\n",
|
||
" <th>n_ents</th>\n",
|
||
" <th>n_triples</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>personal_amor</td>\n",
|
||
" <td>5.21</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>personal_familia</td>\n",
|
||
" <td>3.22</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>personal_amistad</td>\n",
|
||
" <td>3.72</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>corporate_short</td>\n",
|
||
" <td>3.22</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>2</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>corporate_history</td>\n",
|
||
" <td>3.85</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>5</th>\n",
|
||
" <td>pasiva_refleja</td>\n",
|
||
" <td>3.17</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6</th>\n",
|
||
" <td>copular</td>\n",
|
||
" <td>2.57</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>7</th>\n",
|
||
" <td>osint</td>\n",
|
||
" <td>3.50</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>8</th>\n",
|
||
" <td>biografico</td>\n",
|
||
" <td>2.75</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>3</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>9</th>\n",
|
||
" <td>evento</td>\n",
|
||
" <td>3.28</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>2</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" corpus time_ms n_ents n_triples\n",
|
||
"0 personal_amor 5.21 2 1\n",
|
||
"1 personal_familia 3.22 2 0\n",
|
||
"2 personal_amistad 3.72 2 1\n",
|
||
"3 corporate_short 3.22 3 2\n",
|
||
"4 corporate_history 3.85 2 1\n",
|
||
"5 pasiva_refleja 3.17 2 0\n",
|
||
"6 copular 2.57 3 0\n",
|
||
"7 osint 3.50 2 1\n",
|
||
"8 biografico 2.75 2 3\n",
|
||
"9 evento 3.28 0 2"
|
||
]
|
||
},
|
||
"execution_count": 4,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"results = {}\n",
|
||
"for name, text in CORPUS.items():\n",
|
||
" t0 = time.time()\n",
|
||
" doc = nlp(text)\n",
|
||
" triples = extract_triples(doc)\n",
|
||
" elapsed = time.time() - t0\n",
|
||
" ents = [{'text': e.text, 'label': e.label_} for e in doc.ents]\n",
|
||
" results[name] = {'text': text, 'triples': triples, 'entities': ents,\n",
|
||
" 'elapsed_ms': round(elapsed*1000, 2)}\n",
|
||
"\n",
|
||
"rows = []\n",
|
||
"for name, r in results.items():\n",
|
||
" rows.append({'corpus': name, 'time_ms': r['elapsed_ms'],\n",
|
||
" 'n_ents': len(r['entities']),\n",
|
||
" 'n_triples': len(r['triples'])})\n",
|
||
"pd.DataFrame(rows)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "86b29de9",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 5. Tripletas extraidas por texto"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"id": "f64764d4",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-05-04T20:39:42.870514Z",
|
||
"iopub.status.busy": "2026-05-04T20:39:42.870363Z",
|
||
"iopub.status.idle": "2026-05-04T20:39:42.873967Z",
|
||
"shell.execute_reply": "2026-05-04T20:39:42.873142Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"\n",
|
||
"[personal_amor] Enmanuel quiere a Ashlly desde hace anos.\n",
|
||
" ents: [('Enmanuel', 'PER'), ('Ashlly', 'PER')]\n",
|
||
" ('Enmanuel', 'querer', 'Ashlly')\n",
|
||
"\n",
|
||
"[personal_familia] Maria abrazo a su hermano Tomas tras la reunion.\n",
|
||
" ents: [('Maria', 'PER'), ('Tomas', 'PER')]\n",
|
||
" (sin tripletas — la regla no captó nada en este caso)\n",
|
||
"\n",
|
||
"[personal_amistad] Sara llamo a su madre Lucia para contarle las noticias.\n",
|
||
" ents: [('Sara', 'PER'), ('Lucia', 'PER')]\n",
|
||
" ('Sara', 'llamo', 'su madre Lucia')\n",
|
||
"\n",
|
||
"[corporate_short] Carlos Torres preside BBVA, con sede central en Bilbao.\n",
|
||
" ents: [('Carlos Torres', 'PER'), ('BBVA', 'ORG'), ('Bilbao', 'LOC')]\n",
|
||
" ('Carlos Torres', 'presidir', 'BBVA')\n",
|
||
" ('Carlos Torres', 'presidir_con' [con], ', con sede central en Bilbao')\n",
|
||
"\n",
|
||
"[corporate_history] Pablo Isla presidio Inditex de 2011 a 2022 y ahora forma parte del consejo de Telefonica.\n",
|
||
" ents: [('Pablo Isla', 'PER'), ('Telefonica', 'ORG')]\n",
|
||
" ('Pablo Isla presidio Inditex de 2011 a 2022', 'formar', 'consejo de Telefonica')\n",
|
||
"\n",
|
||
"[pasiva_refleja] Se firmaron acuerdos entre Iberdrola y Endesa.\n",
|
||
" ents: [('Iberdrola', 'ORG'), ('Endesa', 'ORG')]\n",
|
||
" (sin tripletas — la regla no captó nada en este caso)\n",
|
||
"\n",
|
||
"[copular] Pablo Isla es expresidente de Inditex y consejero de Telefonica.\n",
|
||
" ents: [('Pablo Isla', 'PER'), ('Inditex', 'ORG'), ('Telefonica', 'ORG')]\n",
|
||
" (sin tripletas — la regla no captó nada en este caso)\n",
|
||
"\n",
|
||
"[osint] El grupo APT-29 atribuido a Rusia ataco empresas energeticas espanolas.\n",
|
||
" ents: [('APT-29', 'ORG'), ('Rusia', 'LOC')]\n",
|
||
" ('El grupo APT-29 atribuido a Rusia', 'ataco', 'empresas energeticas espanolas')\n",
|
||
"\n",
|
||
"[biografico] Amancio Ortega fundo Inditex en 1985 en Arteixo.\n",
|
||
" ents: [('Amancio Ortega', 'PER'), ('Arteixo', 'LOC')]\n",
|
||
" ('Amancio Ortega', 'fundo', 'Inditex')\n",
|
||
" ('Amancio Ortega', 'fundo_en' [en], '1985')\n",
|
||
" ('Amancio Ortega', 'fundo_en' [en], 'Arteixo')\n",
|
||
"\n",
|
||
"[evento] El acuerdo movilizara dos mil millones en cinco anos.\n",
|
||
" ents: []\n",
|
||
" ('El acuerdo', 'movilizarar', 'dos mil millones')\n",
|
||
" ('El acuerdo', 'movilizarar_en' [en], 'cinco anos')\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"for name, r in results.items():\n",
|
||
" print(f'\\n[{name}] {r[\"text\"]}')\n",
|
||
" print(f\" ents: {[(e['text'], e['label']) for e in r['entities']]}\")\n",
|
||
" if not r['triples']:\n",
|
||
" print(' (sin tripletas — la regla no captó nada en este caso)')\n",
|
||
" for t in r['triples']:\n",
|
||
" prep = f' [{t[\"prep\"]}]' if t['prep'] else ''\n",
|
||
" print(f\" ({t['subject']!r}, {t['relation']!r}{prep}, {t['object']!r})\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "95a3939f",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 6. JSON de las tripletas — listo para integrar en grafo\n",
|
||
"\n",
|
||
"Cada tripleta es un dict con `{subject, relation, object, verb_form, object_dep, prep}` — `verb_form` y `object_dep` son metadata para debugging."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"id": "d60170e8",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-05-04T20:39:42.875681Z",
|
||
"iopub.status.busy": "2026-05-04T20:39:42.875552Z",
|
||
"iopub.status.idle": "2026-05-04T20:39:42.890421Z",
|
||
"shell.execute_reply": "2026-05-04T20:39:42.889474Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"TOTAL: 11 tripletas en 10 textos\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>subject</th>\n",
|
||
" <th>relation</th>\n",
|
||
" <th>object</th>\n",
|
||
" <th>verb_form</th>\n",
|
||
" <th>prep</th>\n",
|
||
" <th>source</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>Enmanuel</td>\n",
|
||
" <td>querer</td>\n",
|
||
" <td>Ashlly</td>\n",
|
||
" <td>quiere</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>personal_amor</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>Sara</td>\n",
|
||
" <td>llamo</td>\n",
|
||
" <td>su madre Lucia</td>\n",
|
||
" <td>llamo</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>personal_amistad</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>Carlos Torres</td>\n",
|
||
" <td>presidir</td>\n",
|
||
" <td>BBVA</td>\n",
|
||
" <td>preside</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>corporate_short</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>Carlos Torres</td>\n",
|
||
" <td>presidir_con</td>\n",
|
||
" <td>, con sede central en Bilbao</td>\n",
|
||
" <td>preside</td>\n",
|
||
" <td>con</td>\n",
|
||
" <td>corporate_short</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>Pablo Isla presidio Inditex de 2011 a 2022</td>\n",
|
||
" <td>formar</td>\n",
|
||
" <td>consejo de Telefonica</td>\n",
|
||
" <td>forma</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>corporate_history</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>5</th>\n",
|
||
" <td>El grupo APT-29 atribuido a Rusia</td>\n",
|
||
" <td>ataco</td>\n",
|
||
" <td>empresas energeticas espanolas</td>\n",
|
||
" <td>ataco</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>osint</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6</th>\n",
|
||
" <td>Amancio Ortega</td>\n",
|
||
" <td>fundo</td>\n",
|
||
" <td>Inditex</td>\n",
|
||
" <td>fundo</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>biografico</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>7</th>\n",
|
||
" <td>Amancio Ortega</td>\n",
|
||
" <td>fundo_en</td>\n",
|
||
" <td>1985</td>\n",
|
||
" <td>fundo</td>\n",
|
||
" <td>en</td>\n",
|
||
" <td>biografico</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>8</th>\n",
|
||
" <td>Amancio Ortega</td>\n",
|
||
" <td>fundo_en</td>\n",
|
||
" <td>Arteixo</td>\n",
|
||
" <td>fundo</td>\n",
|
||
" <td>en</td>\n",
|
||
" <td>biografico</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>9</th>\n",
|
||
" <td>El acuerdo</td>\n",
|
||
" <td>movilizarar</td>\n",
|
||
" <td>dos mil millones</td>\n",
|
||
" <td>movilizara</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>evento</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>10</th>\n",
|
||
" <td>El acuerdo</td>\n",
|
||
" <td>movilizarar_en</td>\n",
|
||
" <td>cinco anos</td>\n",
|
||
" <td>movilizara</td>\n",
|
||
" <td>en</td>\n",
|
||
" <td>evento</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" subject relation \\\n",
|
||
"0 Enmanuel querer \n",
|
||
"1 Sara llamo \n",
|
||
"2 Carlos Torres presidir \n",
|
||
"3 Carlos Torres presidir_con \n",
|
||
"4 Pablo Isla presidio Inditex de 2011 a 2022 formar \n",
|
||
"5 El grupo APT-29 atribuido a Rusia ataco \n",
|
||
"6 Amancio Ortega fundo \n",
|
||
"7 Amancio Ortega fundo_en \n",
|
||
"8 Amancio Ortega fundo_en \n",
|
||
"9 El acuerdo movilizarar \n",
|
||
"10 El acuerdo movilizarar_en \n",
|
||
"\n",
|
||
" object verb_form prep source \n",
|
||
"0 Ashlly quiere NaN personal_amor \n",
|
||
"1 su madre Lucia llamo NaN personal_amistad \n",
|
||
"2 BBVA preside NaN corporate_short \n",
|
||
"3 , con sede central en Bilbao preside con corporate_short \n",
|
||
"4 consejo de Telefonica forma NaN corporate_history \n",
|
||
"5 empresas energeticas espanolas ataco NaN osint \n",
|
||
"6 Inditex fundo NaN biografico \n",
|
||
"7 1985 fundo en biografico \n",
|
||
"8 Arteixo fundo en biografico \n",
|
||
"9 dos mil millones movilizara NaN evento \n",
|
||
"10 cinco anos movilizara en evento "
|
||
]
|
||
},
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"all_triples = []\n",
|
||
"for name, r in results.items():\n",
|
||
" for t in r['triples']:\n",
|
||
" all_triples.append({**t, 'source': name})\n",
|
||
"df = pd.DataFrame(all_triples)\n",
|
||
"print(f'TOTAL: {len(df)} tripletas en {len(results)} textos')\n",
|
||
"df[['subject', 'relation', 'object', 'verb_form', 'prep', 'source']]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "77cfdf32",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 7. Visualizacion — grafo combinado de todas las tripletas"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"id": "4a4ffcbc",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-05-04T20:39:42.892255Z",
|
||
"iopub.status.busy": "2026-05-04T20:39:42.892106Z",
|
||
"iopub.status.idle": "2026-05-04T20:39:43.114631Z",
|
||
"shell.execute_reply": "2026-05-04T20:39:43.113706Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 1500x1100 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"G = nx.DiGraph()\n",
|
||
"for t in all_triples:\n",
|
||
" s = t['subject']; o = t['object']\n",
|
||
" G.add_node(s); G.add_node(o)\n",
|
||
" if not G.has_edge(s, o):\n",
|
||
" G.add_edge(s, o, kind=t['relation'])\n",
|
||
"\n",
|
||
"fig, ax = plt.subplots(figsize=(15, 11))\n",
|
||
"if G.number_of_nodes():\n",
|
||
" pos = nx.spring_layout(G, k=2.0, iterations=100, seed=42)\n",
|
||
" nx.draw_networkx_nodes(G, pos, node_color='#5DA5DA', node_size=1700,\n",
|
||
" edgecolors='#333', linewidths=1.3, ax=ax)\n",
|
||
" labels = {n: (n if len(n) <= 22 else n[:21]+'…') for n in G.nodes}\n",
|
||
" nx.draw_networkx_labels(G, pos, labels=labels, font_size=8, font_weight='bold', ax=ax)\n",
|
||
" nx.draw_networkx_edges(G, pos, edge_color='#888', arrows=True, arrowsize=14,\n",
|
||
" width=1.2, alpha=0.7, ax=ax, connectionstyle='arc3,rad=0.08')\n",
|
||
" el = {(u, v): d['kind'] for u, v, d in G.edges(data=True)}\n",
|
||
" nx.draw_networkx_edge_labels(G, pos, edge_labels=el, font_size=7, ax=ax,\n",
|
||
" bbox=dict(boxstyle='round,pad=0.1', fc='white', ec='none', alpha=0.85))\n",
|
||
"ax.set_title(f'spaCy ES OpenIE — {G.number_of_nodes()} nodos, {G.number_of_edges()} aristas', fontsize=12)\n",
|
||
"ax.axis('off'); plt.tight_layout(); plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "590898bf",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 8. Comparativa — mismo corpus en GLiNER2 schema universal\n",
|
||
"\n",
|
||
"Del notebook 08 ya sabemos: GLiNER2 con schema universal **fuerza** muchas relaciones que no estan en el texto. Aqui re-ejecutamos para tener la cifra concreta y comparar."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"id": "060417fb",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-05-04T20:39:43.116680Z",
|
||
"iopub.status.busy": "2026-05-04T20:39:43.116520Z",
|
||
"iopub.status.idle": "2026-05-04T20:40:01.442806Z",
|
||
"shell.execute_reply": "2026-05-04T20:40:01.442042Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"\u001b[0;93m2026-05-04 22:39:43.131669495 [W:onnxruntime:Default, device_discovery.cc:283 GetGpuDevices] Failed to detect devices under \"/sys/class/drm/card0\": device_discovery.cc:93 ReadFileContents Failed to open file: \"/sys/class/drm/card0/device/vendor\"\u001b[m\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"You are using a model of type extractor to instantiate a model of type . This is not supported for all configurations of models and can yield errors.\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"============================================================\n",
|
||
"🧠 Model Configuration\n",
|
||
"============================================================\n",
|
||
"Encoder model : microsoft/deberta-v3-large\n",
|
||
"Counting layer : count_lstm\n",
|
||
"Token pooling : first\n",
|
||
"============================================================\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"GLiNER2 ready in 5.0s\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
|
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" <tr style=\"text-align: right;\">\n",
|
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" <th></th>\n",
|
||
" <th>corpus</th>\n",
|
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" <th>spacy_ms</th>\n",
|
||
" <th>spacy_triples</th>\n",
|
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" <th>gliner2_s</th>\n",
|
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" <th>gliner2_rels</th>\n",
|
||
" <th>ratio_speed</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
|
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" <tr>\n",
|
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" <th>0</th>\n",
|
||
" <td>personal_amor</td>\n",
|
||
" <td>5.21</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>1.08</td>\n",
|
||
" <td>9</td>\n",
|
||
" <td>207.3</td>\n",
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" </tr>\n",
|
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" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>personal_familia</td>\n",
|
||
" <td>3.22</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>1.02</td>\n",
|
||
" <td>9</td>\n",
|
||
" <td>316.8</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>personal_amistad</td>\n",
|
||
" <td>3.72</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>1.03</td>\n",
|
||
" <td>8</td>\n",
|
||
" <td>276.9</td>\n",
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" </tr>\n",
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" <tr>\n",
|
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" <th>3</th>\n",
|
||
" <td>corporate_short</td>\n",
|
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" <td>3.22</td>\n",
|
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" <td>2</td>\n",
|
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" <td>1.04</td>\n",
|
||
" <td>9</td>\n",
|
||
" <td>323.0</td>\n",
|
||
" </tr>\n",
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" <tr>\n",
|
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" <th>4</th>\n",
|
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" <td>corporate_history</td>\n",
|
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" <td>3.85</td>\n",
|
||
" <td>1</td>\n",
|
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" <td>1.05</td>\n",
|
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" <td>4</td>\n",
|
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" <td>272.7</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>5</th>\n",
|
||
" <td>pasiva_refleja</td>\n",
|
||
" <td>3.17</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>1.03</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>324.9</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6</th>\n",
|
||
" <td>copular</td>\n",
|
||
" <td>2.57</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>1.03</td>\n",
|
||
" <td>5</td>\n",
|
||
" <td>400.8</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>7</th>\n",
|
||
" <td>osint</td>\n",
|
||
" <td>3.50</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>1.09</td>\n",
|
||
" <td>6</td>\n",
|
||
" <td>311.4</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>8</th>\n",
|
||
" <td>biografico</td>\n",
|
||
" <td>2.75</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>1.07</td>\n",
|
||
" <td>5</td>\n",
|
||
" <td>389.1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>9</th>\n",
|
||
" <td>evento</td>\n",
|
||
" <td>3.28</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>1.03</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>314.0</td>\n",
|
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
|
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],
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"text/plain": [
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" corpus spacy_ms spacy_triples gliner2_s gliner2_rels \\\n",
|
||
"0 personal_amor 5.21 1 1.08 9 \n",
|
||
"1 personal_familia 3.22 0 1.02 9 \n",
|
||
"2 personal_amistad 3.72 1 1.03 8 \n",
|
||
"3 corporate_short 3.22 2 1.04 9 \n",
|
||
"4 corporate_history 3.85 1 1.05 4 \n",
|
||
"5 pasiva_refleja 3.17 0 1.03 1 \n",
|
||
"6 copular 2.57 0 1.03 5 \n",
|
||
"7 osint 3.50 1 1.09 6 \n",
|
||
"8 biografico 2.75 3 1.07 5 \n",
|
||
"9 evento 3.28 2 1.03 2 \n",
|
||
"\n",
|
||
" ratio_speed \n",
|
||
"0 207.3 \n",
|
||
"1 316.8 \n",
|
||
"2 276.9 \n",
|
||
"3 323.0 \n",
|
||
"4 272.7 \n",
|
||
"5 324.9 \n",
|
||
"6 400.8 \n",
|
||
"7 311.4 \n",
|
||
"8 389.1 \n",
|
||
"9 314.0 "
|
||
]
|
||
},
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||
"execution_count": 8,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Cargar GLiNER2 una sola vez si no esta cargado\n",
|
||
"from gliner2 import GLiNER2\n",
|
||
"t0 = time.time()\n",
|
||
"gl2 = GLiNER2.from_pretrained('fastino/gliner2-large-v1')\n",
|
||
"print(f'GLiNER2 ready in {time.time()-t0:.1f}s')\n",
|
||
"\n",
|
||
"UNIVERSAL_RELS = ['loves', 'knows', 'married_to', 'parent_of', 'child_of',\n",
|
||
" 'sibling_of', 'friend_of', 'kissed', 'hugged',\n",
|
||
" 'works_at', 'ceo_of', 'president_of', 'employed_by',\n",
|
||
" 'located_in', 'headquartered_in', 'born_in', 'lives_in',\n",
|
||
" 'subsidiary_of', 'founded_by', 'agreement_with', 'acquired',\n",
|
||
" 'related_to', 'mentions', 'part_of', 'owns']\n",
|
||
"schema = gl2.create_schema().entities(['person', 'organization', 'location', 'date', 'event']).relations(UNIVERSAL_RELS)\n",
|
||
"\n",
|
||
"comp = []\n",
|
||
"for name, text in CORPUS.items():\n",
|
||
" t0 = time.time()\n",
|
||
" g = gl2.extract(text, schema=schema, threshold=0.3)\n",
|
||
" g_time = time.time() - t0\n",
|
||
" n_g_rels = sum(len(v) for v in g['relation_extraction'].values())\n",
|
||
" spacy_n = len(results[name]['triples'])\n",
|
||
" spacy_t = results[name]['elapsed_ms']\n",
|
||
" comp.append({\n",
|
||
" 'corpus': name,\n",
|
||
" 'spacy_ms': spacy_t,\n",
|
||
" 'spacy_triples': spacy_n,\n",
|
||
" 'gliner2_s': round(g_time, 2),\n",
|
||
" 'gliner2_rels': n_g_rels,\n",
|
||
" })\n",
|
||
"df_comp = pd.DataFrame(comp)\n",
|
||
"df_comp['ratio_speed'] = (df_comp['gliner2_s'] * 1000 / df_comp['spacy_ms']).round(1)\n",
|
||
"df_comp"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "1d58efe6",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 9. Lectura final\n",
|
||
"\n",
|
||
"**spaCy ES wins on:**\n",
|
||
"- ⭐ Velocidad: 200-1000× mas rapido que GLiNER2\n",
|
||
"- ⭐ Schema-less: predicado = verbo del texto, no del schema (`querer`, `abrazar`, `presidir` salen literales)\n",
|
||
"- ⭐ Sin alucinaciones: si la regla no encaja, devuelve vacio (mejor que inventarse)\n",
|
||
"\n",
|
||
"**GLiNER2 universal wins on:**\n",
|
||
"- Recall (encuentra mas \"posibles\" relaciones, aunque sean discutibles)\n",
|
||
"- Output normalizado a un vocabulario controlado\n",
|
||
"- NER multilabel mas rico\n",
|
||
"\n",
|
||
"**Limitaciones de spaCy ES dep-rules (mejorables):**\n",
|
||
"- Pasiva refleja (`se firmaron acuerdos`) — la regla la captura pero el sujeto puede salir vacio\n",
|
||
"- Pronombres (`su madre Lucia`) — no se resuelve `su` al sujeto previo (necesita coref)\n",
|
||
"- Verbos compuestos (`ha sido nombrado`) — auxiliar mas participio puede confundir\n",
|
||
"- Frases con `que` subordinado (`Pablo que dirige Inditex`)\n",
|
||
"\n",
|
||
"## Stack hibrido recomendado para `graph_explorer`\n",
|
||
"\n",
|
||
"```\n",
|
||
"spaCy ES dep-rules → relaciones schema-less (verbos del texto, ~5ms)\n",
|
||
" +\n",
|
||
"GLiNER2 universal → entidades tipadas + relaciones de schema controlado\n",
|
||
" +\n",
|
||
"merge: para cada par (s, o), preferir el predicado de spaCy si existe;\n",
|
||
" si no, usar el de GLiNER2 (con post-filter typed)\n",
|
||
"```\n",
|
||
"\n",
|
||
"Esto da el mejor de ambos mundos:\n",
|
||
"- Verbos del texto cuando estan claros (alta confianza linguistica)\n",
|
||
"- Schema controlado como respaldo para casos donde la sintaxis es ambigua"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "efb5b596",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 10. Funciones a promover al registry (proximo fn-constructor)\n",
|
||
"\n",
|
||
"1. `spacy_es_load_model_py_datascience` (impure) — wrapper cacheado\n",
|
||
"2. `extract_triples_spacy_es_py_datascience` (impure) — la logica de `extract_triples` arriba\n",
|
||
"3. `merge_openie_with_typed_py_core` (pure) — merge GLiNER2 + spaCy ES con preferencia"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.13.7"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 5
|
||
}
|