egutierrez fa5bcca155 feat(datascience): GLiREL relation extractor (zero-shot triplets) drop-in con LLM ...

- glirel_load_model: cache por (model_name, device); device='auto' resuelve via torch
- extract_relations_glirel: tokeniza por whitespace, mapea spans char->token,
  llama predict_relations y devuelve RelationCandidate; fallback text.find si la
  entidad llega sin offsets; max_pairs=N -> top-N por score
- pyproject.toml: glirel en extra nlp

Closes #0039

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

2026-04-30 16:41:09 +02:00

..

tests

test(datascience): corpus stub para gliner_load_model + extract_entities_gliner

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__init__.py

feat: funciones Python para core, cybersecurity, datascience y finance

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aggregate_by_group_test.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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aggregate_by_group.md

docs: params/output semántico en 506 funciones para composabilidad

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aggregate_by_group.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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autocorrelation.md

docs: params/output semántico en 506 funciones para composabilidad

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build_entity_schema_prompt_test.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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build_entity_schema_prompt.md

docs: params/output semántico en 506 funciones para composabilidad

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build_entity_schema_prompt.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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build_relation_schema_prompt_test.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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build_relation_schema_prompt.md

docs: params/output semántico en 506 funciones para composabilidad

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build_relation_schema_prompt.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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clip.md

docs: params/output semántico en 506 funciones para composabilidad

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datascience.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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deduplicate_entities_test.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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deduplicate_entities.md

docs: params/output semántico en 506 funciones para composabilidad

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deduplicate_entities.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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deduplicate_relations_test.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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deduplicate_relations.md

docs: params/output semántico en 506 funciones para composabilidad

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deduplicate_relations.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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detect_drift_test.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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detect_drift.md

docs: params/output semántico en 506 funciones para composabilidad

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detect_drift.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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detect_outliers.md

docs: params/output semántico en 506 funciones para composabilidad

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diff_entities_test.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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diff_entities.md

docs: params/output semántico en 506 funciones para composabilidad

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diff_entities.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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diff_relations_test.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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diff_relations.md

docs: params/output semántico en 506 funciones para composabilidad

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diff_relations.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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estimate_hawkes.md

docs: params/output semántico en 506 funciones para composabilidad

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estimate_pareto_alpha.md

docs: params/output semántico en 506 funciones para composabilidad

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extract_entities_gliner.md

feat(datascience): GLiNER entity extractor (zero-shot NER) drop-in con LLM

2026-04-30 16:33:38 +02:00

extract_entities_gliner.py

feat(datascience): GLiNER entity extractor (zero-shot NER) drop-in con LLM

2026-04-30 16:33:38 +02:00

extract_entities_llm_test.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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extract_entities_llm.md

docs: params/output semántico en 506 funciones para composabilidad

2026-04-05 18:45:16 +02:00

extract_entities_llm.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

2026-04-05 17:11:32 +02:00

extract_relations_glirel.md

feat(datascience): GLiREL relation extractor (zero-shot triplets) drop-in con LLM

2026-04-30 16:41:09 +02:00

extract_relations_glirel.py

feat(datascience): GLiREL relation extractor (zero-shot triplets) drop-in con LLM

2026-04-30 16:41:09 +02:00

extract_relations_llm_test.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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extract_relations_llm.md

docs: params/output semántico en 506 funciones para composabilidad

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extract_relations_llm.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

2026-04-05 17:11:32 +02:00

gliner_load_model.md

feat(datascience): GLiNER entity extractor (zero-shot NER) drop-in con LLM

2026-04-30 16:33:38 +02:00

gliner_load_model.py

feat(datascience): GLiNER entity extractor (zero-shot NER) drop-in con LLM

2026-04-30 16:33:38 +02:00

glirel_load_model.md

feat(datascience): GLiREL relation extractor (zero-shot triplets) drop-in con LLM

2026-04-30 16:41:09 +02:00

glirel_load_model.py

feat(datascience): GLiREL relation extractor (zero-shot triplets) drop-in con LLM

2026-04-30 16:41:09 +02:00

histogram.md

docs: params/output semántico en 506 funciones para composabilidad

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hotness_score_test.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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hotness_score.md

docs: params/output semántico en 506 funciones para composabilidad

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hotness_score.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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impute.md

docs: params/output semántico en 506 funciones para composabilidad

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linspace.md

docs: params/output semántico en 506 funciones para composabilidad

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melt_test.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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melt.md

docs: params/output semántico en 506 funciones para composabilidad

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melt.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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merge_graphs_test.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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merge_graphs.md

docs: params/output semántico en 506 funciones para composabilidad

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merge_graphs.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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min_max_scale.md

docs: params/output semántico en 506 funciones para composabilidad

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ops_to_rdf_triples.md

docs: params/output semántico en 506 funciones para composabilidad

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ops_to_rdf_triples.py

feat: funciones datascience — ops_to_rdf_triples, ops_to_sigma_json, render_sigma_html

2026-04-02 22:03:51 +02:00

ops_to_sigma_json.md

docs: params/output semántico en 506 funciones para composabilidad

2026-04-05 18:45:16 +02:00

ops_to_sigma_json.py

feat: funciones datascience — ops_to_rdf_triples, ops_to_sigma_json, render_sigma_html

2026-04-02 22:03:51 +02:00

pearson.md

docs: params/output semántico en 506 funciones para composabilidad

2026-04-05 18:45:16 +02:00

pivot_test.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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pivot.md

docs: params/output semántico en 506 funciones para composabilidad

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pivot.py

feat: funciones Python datascience, finance, cybersecurity y pipelines

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render_sigma_html.md

docs: params/output semántico en 506 funciones para composabilidad

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render_sigma_html.py

feat: funciones datascience — ops_to_rdf_triples, ops_to_sigma_json, render_sigma_html

2026-04-02 22:03:51 +02:00

rolling_window.md

docs: params/output semántico en 506 funciones para composabilidad

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standardize.md

docs: params/output semántico en 506 funciones para composabilidad

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