Triple

T5286756
Position Surface form Disambiguated ID Type / Status
Subject David and Lisa E119636 entity
Predicate starring P1507 FINISHED
Object Janet Margolin E322442 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: Janet Margolin | Statement: [David and Lisa, starring, Janet Margolin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Janet Margolin
Context triple: [David and Lisa, starring, Janet Margolin]
  • A. Janet Margolin chosen
    Janet Margolin was an American film and television actress best known for her roles in movies such as "David and Lisa" and Woody Allen's "Annie Hall."
  • B. Judy Levitt
    Judy Levitt is an American actress best known for her long marriage to Star Trek actor Walter Koenig and for appearing in several of his film and television projects.
  • C. Nancy Lieberman
    Nancy Lieberman is a pioneering American basketball player and coach, widely regarded as one of the greatest figures in women's basketball history and a trailblazer for women in the sport.
  • D. Barbara Siegel
    Barbara Siegel is an American author best known for co-writing numerous science fiction and fantasy novels and game-related books, often in collaboration with her husband Scott Siegel.
  • E. Liz Gorinsky
    Liz Gorinsky is an acclaimed science fiction and fantasy editor known for her influential work at Tor Books and for winning major genre awards.
  • 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_69bd446de5648190b313a90bd96730d2 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd84d9a0788190a4a85a9cab07903f completed March 20, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfc60964c08190bcb128946e121bc9 completed March 22, 2026, 10:35 a.m.
Created at: March 20, 2026, 1:52 p.m.