Triple

T10324078
Position Surface form Disambiguated ID Type / Status
Subject Angel Torres E242713 entity
Predicate hasFamilyName P18 FINISHED
Object Torres E657102 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Torres | Statement: [Angel Torres, hasFamilyName, Torres]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Torres
Context triple: [Angel Torres, hasFamilyName, Torres]
  • A. Torres chosen
    Torres is a common Spanish surname borne by numerous notable figures across the Spanish-speaking world.
  • B. Sanchez
    Sanchez is a common Spanish-origin surname borne by numerous notable individuals across sports, politics, arts, and other fields.
  • C. Carvajal
    Carvajal is a Spanish surname of likely toponymic origin, borne by various notable figures in Spanish and Latin American history.
  • D. Nando Torres
    Nando Torres is a central character in the family comedy film "Yes Day," portrayed as one of the children whose parents agree to say yes to all of their requests for 24 hours.
  • E. Ramos
    Ramos is a municipality in the Philippine province of Tarlac known for its predominantly agricultural economy and rural communities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d381af787481908bc401325c760a88 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d6ce683c8190bf5385dd04bf2de8 completed April 7, 2026, 10:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71da2053481908fe5ed097b480cdd completed April 9, 2026, 3:31 a.m.
Created at: April 6, 2026, 11:51 a.m.