Triple

T19865258
Position Surface form Disambiguated ID Type / Status
Subject Emily Davison E477373 entity
Predicate hasNotableArrest P125272 FINISHED
Object multiple arrests for suffragette activities 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: multiple arrests for suffragette activities | Statement: [Emily Davison, hasNotableArrest, multiple arrests for suffragette activities]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasNotableArrest
Context triple: [Emily Davison, hasNotableArrest, multiple arrests for suffragette activities]
  • A. hasBeenArrestedBy
    Indicates that an entity has been taken into custody or formally apprehended by another entity, typically a law enforcement authority.
  • B. notableArrests chosen
    Indicates that an entity has been arrested in a way considered significant or noteworthy, typically due to the circumstances, impact, or public attention surrounding the arrest.
  • C. hasReasonForArrest
    Indicates that an arrest is associated with a specific reason or cause.
  • D. notableArrestee
    Indicates that the subject is a person who was arrested in a way considered notable or significant, typically in connection with the object (such as an event, case, or authority).
  • E. hasHadCriminalConviction
    Indicates that an entity has previously been found guilty of a criminal offense through a legal process.
  • 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_69d8e51e7d948190aedbcd6c30361c39 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6589eb24081908715b683de1edc68 completed April 20, 2026, 4:47 p.m.
PD Predicate disambiguation batch_69e537e8c4e481909fe95d795b4864e7 completed April 19, 2026, 8:15 p.m.
Created at: April 10, 2026, 1:51 p.m.