Triple

T3854944
Position Surface form Disambiguated ID Type / Status
Subject Lady in the Water E89989 entity
Predicate castMember P1668 FINISHED
Object Jared Harris E187118 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: Jared Harris | Statement: [Lady in the Water, castMember, Jared Harris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jared Harris
Context triple: [Lady in the Water, castMember, Jared Harris]
  • A. Jared Harris chosen
    Jared Harris is a British actor known for his character roles in film and television, including acclaimed performances in series like "Mad Men," "Chernobyl," and "The Crown."
  • B. Damian Lewis
    Damian Lewis is a British actor known for his acclaimed performances in television dramas such as "Homeland" and "Band of Brothers."
  • C. Holt McCallany
    Holt McCallany is an American actor best known for his tough, authoritative roles in film and television, including a prominent turn as FBI agent Bill Tench in the series "Mindhunter."
  • D. Lewis Pullman
    Lewis Pullman is an American actor known for roles in films such as "Top Gun: Maverick," "Bad Times at the El Royale," and "The Strangers: Prey at Night."
  • E. Dylan Baker
    Dylan Baker is an American character actor known for his versatile roles in film, television, and theater, including appearances in movies like "Planes, Trains and Automobiles" and the "Spider-Man" series.
  • 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_69aed95b3c088190a8f85d19e6070599 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec05ec4c8190bd5e5463163712dc completed March 9, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c3151e8819082d72756875a9b1d completed March 14, 2026, 11:53 a.m.
Created at: March 9, 2026, 3:19 p.m.