Triple

T12135506
Position Surface form Disambiguated ID Type / Status
Subject Téa Leoni E289044 entity
Predicate notableWork P4 FINISHED
Object The Family Man E381869 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: The Family Man | Statement: [Téa Leoni, notableWork, The Family Man]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Family Man
Context triple: [Téa Leoni, notableWork, The Family Man]
  • A. The Family Man chosen
    The Family Man is a 2000 romantic fantasy drama film starring Nicolas Cage as a high-powered executive who gets a glimpse of an alternate life as a family man.
  • B. The Family Man
    The Family Man is a British television drama series in which Rupert Graves plays a central role in a story about the complexities of modern family life.
  • C. Man of the House
    Man of the House is a 1995 family comedy film starring Chevy Chase and Jonathan Taylor Thomas about a boy who schemes to get rid of his mother's new boyfriend.
  • D. Man of the House
    Man of the House is the political memoir of longtime U.S. Speaker of the House Tip O’Neill, recounting his career in Congress and his views on American politics.
  • E. Fukrey
    Fukrey is a popular 2013 Indian Hindi-language comedy film about a group of slackers in Delhi whose get-rich-quick schemes lead to chaotic and humorous consequences.
  • 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_69d6ab4b5e4c81909950b17151eb0951 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9158c59e0819094d4522a107482b2 completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f68eab98819086a480a90312c3fe completed May 2, 2026, 1:05 p.m.
Created at: April 8, 2026, 9:49 p.m.