Triple

T9722422
Position Surface form Disambiguated ID Type / Status
Subject Arlene Dahl E235508 entity
Predicate spouse P13 FINISHED
Object Fernando Lamas E578107 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: Fernando Lamas | Statement: [Arlene Dahl, spouse, Fernando Lamas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fernando Lamas
Context triple: [Arlene Dahl, spouse, Fernando Lamas]
  • A. Fernando Lamas chosen
    Fernando Lamas was an Argentine-American actor and director known for his suave, romantic leading roles in Hollywood films of the 1950s.
  • B. Mel Ferrer
    Mel Ferrer was an American actor, director, and producer known for his work in classic Hollywood films and his marriage to Audrey Hepburn.
  • C. Antonio Camargo
    Antonio Camargo is a Mexican geophysicist known for co-discovering the Chicxulub impact crater linked to the mass extinction of the dinosaurs.
  • D. Francisco Rabal
    Francisco Rabal was a renowned Spanish actor known for his powerful performances in European cinema, particularly in the mid-20th century.
  • E. Fernando Rey
    Fernando Rey was a distinguished Spanish actor renowned for his sophisticated screen presence and memorable roles in European and international cinema, including collaborations with director Luis Buñuel.
  • 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_69ca84d0123c819096f9dc3b6abb0881 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9e75abd48190a6e6679ec51496e8 completed April 1, 2026, 10:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19fa5a8e48190b7b1742eb6c3b81e completed April 4, 2026, 11:32 p.m.
Created at: March 30, 2026, 8:20 p.m.