Triple

T13650419
Position Surface form Disambiguated ID Type / Status
Subject Lord Lieutenant of Herefordshire E326718 entity
Predicate officeContestedInElection P8400 FINISHED
Object false 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: false | Statement: [Lord Lieutenant of Herefordshire, officeContestedInElection, false]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: officeContestedInElection
Context triple: [Lord Lieutenant of Herefordshire, officeContestedInElection, false]
  • A. officeContestedInPresidentialRace
    Indicates that a particular office is being sought or competed for within the context of a presidential election race.
  • B. hasOfficeContested
    Indicates that an individual has been a candidate for a particular public office in an election.
  • C. fictionalOfficeContested
    Indicates that a fictional political or organizational office is being sought or competed for by one or more characters within a narrative.
  • D. wasContestedIn chosen
    Indicates that an event, position, or decision was the subject of competition, dispute, or challenge within a particular context or proceeding.
  • E. alsoContestedIn
    Indicates that the same issue, claim, or matter is being disputed or challenged in another context, case, or proceeding as well.
  • 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_69d8076d8270819092afc2f0e9c359a8 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc608466c81908f6d2c9c92cc86aa completed April 12, 2026, 4:19 p.m.
PD Predicate disambiguation batch_69dbbe8a027081908d8f884b89707a5e completed April 12, 2026, 3:47 p.m.
Created at: April 9, 2026, 9:52 p.m.