Triple

T13547995
Position Surface form Disambiguated ID Type / Status
Subject Anywhere but Here E323563 entity
Predicate narrator P2181 FINISHED
Object Ann August E1046167 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: Ann August | Statement: [Anywhere but Here, narrator, Ann August]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ann August
Context triple: [Anywhere but Here, narrator, Ann August]
  • A. Ann August chosen
    Ann August is the teenage protagonist of Mona Simpson's novel "Anywhere but Here," known for her complex, often strained relationship with her ambitious and eccentric mother as they search for a better life in California.
  • B. Julie
    Julie is a feminine given name of Latin origin, commonly used in many Western countries.
  • C. Pieces of April
    Pieces of April is a 2003 indie dramedy film about a young woman hosting a tense Thanksgiving dinner for her estranged family in a cramped New York City apartment.
  • D. Marnie
    Marnie is the given name of Darcey Bussell, the renowned British ballerina and former principal dancer of The Royal Ballet.
  • E. Marnie
    Marnie is a 1964 psychological thriller film directed by Alfred Hitchcock, starring Tippi Hedren and Sean Connery, about a troubled woman with a mysterious past and compulsive thieving.
  • 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_69d8076776248190bdf0d4fa1f85a5fc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafdcecf481909999a173b32a58cd completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76bae316081909e048ead31a9575a completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:45 p.m.