Triple

T7950446
Position Surface form Disambiguated ID Type / Status
Subject Austin Warren E184599 entity
Predicate portrayedBy P1507 FINISHED
Object Jeffery Wood E712117 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: Jeffery Wood | Statement: [Austin Warren, portrayedBy, Jeffery Wood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeffery Wood
Context triple: [Austin Warren, portrayedBy, Jeffery Wood]
  • A. Jeffery Wood chosen
    Jeffery Wood is an American actor best known for his role on the television sitcom "In the House."
  • B. Timothy Busfield
    Timothy Busfield is an American actor and director best known for his roles in television series such as "thirtysomething," "The West Wing," and various film and stage productions.
  • C. Leo Willis
    Leo Willis was an American character actor active during the silent and early sound film eras, often appearing in comedies alongside stars like Harold Lloyd.
  • D. Jeffrey Dean
    Jeffrey Dean is a prominent American computer scientist and software engineer best known for his influential work on large-scale distributed systems and infrastructure at Google.
  • E. Michael Pennington
    Michael Pennington is a distinguished English actor and director, particularly renowned for his work in classical theatre and Shakespearean performance.
  • 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_69ca8292cba881908a64427b938dac47 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3b5b7450819091e4e6f21e9d832d completed March 31, 2026, 3:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbdf7679881909a14c4786c8e3e76 completed April 1, 2026, 6:40 a.m.
Created at: March 30, 2026, 5:10 p.m.