Triple

T25387860
Position Surface form Disambiguated ID Type / Status
Subject Tit-Willow E631572 entity
Predicate hasCharacterMentioned P162879 FINISHED
Object tom-tit LITERAL 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: tom-tit | Statement: [Tit-Willow, hasCharacterMentioned, tom-tit]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCharacterMentioned
Context triple: [Tit-Willow, hasCharacterMentioned, tom-tit]
  • A. hasMainCharacterDiscussed
    Indicates that the main character has engaged in a discussion or conversation about a particular subject or with another entity.
  • B. eraMentioned
    Indicates that a specific historical or temporal era is explicitly referenced or mentioned in a given context.
  • C. hasCharacterNamedAfter
    Indicates that one entity has a character whose name is derived from or intentionally based on another entity.
  • D. containsCharacterAction
    Indicates that an entity includes or features an action performed by a character within it.
  • E. hasHumanCharacterRole
    Indicates that an entity is assigned a role or function specifically associated with a human character within a context such as a story, performance, or representation.
  • F. None of above. chosen

Provenance (4 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_69e75a8c50788190aabaa9f96710fc43 completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f62e83045c8190a424a2e401a88e9e completed May 2, 2026, 5:04 p.m.
PD Predicate disambiguation batch_69f62c1379f08190836c3e02b0c892df completed May 2, 2026, 4:53 p.m.
PDg Predicate description generation batch_69f62d886828819080ec2f742b9449e3 completed May 2, 2026, 4:59 p.m.
Created at: April 21, 2026, 1:47 p.m.