Triple

T10426410
Position Surface form Disambiguated ID Type / Status
Subject Pearl Harbor (2001 film) E245799 entity
Predicate castMember P1668 FINISHED
Object Jennifer Garner E36244 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: Jennifer Garner | Statement: [Pearl Harbor (2001 film), castMember, Jennifer Garner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jennifer Garner
Context triple: [Pearl Harbor (2001 film), castMember, Jennifer Garner]
  • A. Jennifer Garner chosen
    Jennifer Garner is an American actress known for her starring role in the television series "Alias" and for her performances in films such as "13 Going on 30" and "Dallas Buyers Club."
  • B. Jessica Alba
    Jessica Alba is an American actress and businesswoman known for her roles in films like "Fantastic Four" and for founding the consumer goods company The Honest Company.
  • C. Kate Bosworth
    Kate Bosworth is an American actress best known for her roles in films such as "Blue Crush" and "Superman Returns."
  • D. Katherine Heigl
    Katherine Heigl is an American actress and former fashion model best known for her roles in the television series "Grey's Anatomy" and various romantic comedy films.
  • E. Rachel McAdams
    Rachel McAdams is a Canadian actress known for her versatile performances in films such as "Mean Girls," "The Notebook," and "Spotlight."
  • 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_69d381bf3dc08190bf35a2643e4e8f22 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4ea498ab08190b451c0b257c0711b completed April 7, 2026, 11:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7fc2b50b48190b1d5b29d19a240c2 completed April 9, 2026, 7:21 p.m.
Created at: April 6, 2026, 12:12 p.m.