Triple

T15297046
Position Surface form Disambiguated ID Type / Status
Subject Love, Wedding, Marriage E365686 entity
Predicate hasMainCharacter P1183 FINISHED
Object Ava E1046350 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: Ava | Statement: [Love, Wedding, Marriage, hasMainCharacter, Ava]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ava
Context triple: [Love, Wedding, Marriage, hasMainCharacter, Ava]
  • A. Ava
    Ava was a prominent historical city and royal capital in Upper Burma (now Myanmar), serving as a major political and cultural center for several Burmese kingdoms.
  • B. Ava
    Ava is a feminine given name most famously associated with American actress and Hollywood icon Ava Gardner.
  • C. Ava Alexander chosen
    Ava Alexander is the central protagonist of the film "Up All Night," around whom the story’s main events and character dynamics revolve.
  • D. Ava Quinn
    Ava Quinn is known as one of the children of American actor Aidan Quinn.
  • E. Arielle
    Arielle is a given name shared by various individuals, including Arielle Zuckerberg, a venture capitalist and younger sister of Meta co-founder Mark Zuckerberg.
  • 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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e036848c1881908fbaaae0216d6d27 completed April 16, 2026, 1:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69feef82f6d08190b809260dda247dfe completed May 9, 2026, 8:25 a.m.
Created at: April 10, 2026, 3:15 a.m.