Triple

T15126834
Position Surface form Disambiguated ID Type / Status
Subject Look Back in Anger (1989 television film) E361311 entity
Predicate mainCharacter P1183 FINISHED
Object Alison Porter E420762 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: Alison Porter | Statement: [Look Back in Anger (1989 television film), mainCharacter, Alison Porter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alison Porter
Context triple: [Look Back in Anger (1989 television film), mainCharacter, Alison Porter]
  • A. Alison Porter chosen
    Alison Porter is a central character in John Osborne’s play "Look Back in Anger," portrayed as the emotionally conflicted and long-suffering wife of the protagonist, Jimmy Porter.
  • B. Alison Reid
    Alison Reid is an actress known for her role in the period drama film "Esther Kahn."
  • C. Alison Wright
    Alison Wright is a British actress known for her acclaimed television roles, including standout performances in series such as "The Americans" and "Sneaky Pete."
  • D. Alison Marr
    Alison Marr is a mathematician known for her work in combinatorics and for her contributions to mathematics education and outreach.
  • E. Alison Woods
    Alison Woods is an American actress best known for her role in the horror-comedy film "Detention."
  • 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_69d85a06450081909c5a14ea9851a15e completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e005a1b9288190954f2d92549805e5 completed April 15, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a014132570081909fab220c002c2f10 completed May 11, 2026, 2:38 a.m.
Created at: April 10, 2026, 3:06 a.m.