Triple

T12934971
Position Surface form Disambiguated ID Type / Status
Subject Copenhagen 1801 E309483 entity
Predicate notablePhraseAssociated P53846 FINISHED
Object turning a blind eye 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: turning a blind eye | Statement: [Copenhagen 1801, notablePhraseAssociated, turning a blind eye]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: notablePhraseAssociated
Context triple: [Copenhagen 1801, notablePhraseAssociated, turning a blind eye]
  • A. hasNotablePhrase chosen
    Indicates that an entity is associated with a specific phrase or expression that is considered notable or characteristic of it.
  • B. notableSpeechAssociated
    Indicates that a notable or significant speech is associated with a particular entity, such as a person, event, or location.
  • C. notableExpression
    Indicates that an entity is known for or characterized by a particular expression, gesture, or manner of expression.
  • D. notableQuote
    Indicates that one entity is a significant or well-known quotation attributed to, recorded by, or strongly associated with another entity.
  • E. notablyAssociatedWith
    Indicates that one entity is prominently or distinctively connected with another in a way that is especially noteworthy or remarkable.
  • F. None of above.

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_69d7bdfa933c8190b5a27aa4a08a19b7 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d97e59a4c88190907d05b8d57dae89 completed April 10, 2026, 10:48 p.m.
PD Predicate disambiguation batch_69d97db69f548190a1a693bc0d6c191a completed April 10, 2026, 10:46 p.m.
Created at: April 9, 2026, 5:42 p.m.