Triple

T7336502
Position Surface form Disambiguated ID Type / Status
Subject Joe Lieberman 2004 presidential campaign E169139 entity
Predicate candidatePreviousOffice P72167 FINISHED
Object United States Senator from Connecticut 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: United States Senator from Connecticut | Statement: [Joe Lieberman 2004 presidential campaign, candidatePreviousOffice, United States Senator from Connecticut]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: candidatePreviousOffice
Context triple: [Joe Lieberman 2004 presidential campaign, candidatePreviousOffice, United States Senator from Connecticut]
  • A. previousOffice chosen
    Indicates that one office or position was held immediately before another in a sequence of offices.
  • B. electedOffice
    Indicates that an entity holds or has held a particular office or position as a result of an election.
  • C. officePreviouslyHeldBy
    Indicates that a particular office or position was formerly occupied by a specified person or entity.
  • D. lastIncumbent
    Indicates that the subject is the most recent person or entity to have held a particular position, office, or role before the current one.
  • E. precededByOfficeHolder
    Indicates that one office holder directly held a position before another office holder in a sequence of occupants of the same office.
  • 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_69c68a568a6481908f11e20db7bc8446 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f347f25081908e6086d4073295f5 completed March 27, 2026, 9:14 p.m.
PD Predicate disambiguation batch_69c6f028fd748190b2ea5c3081958a42 completed March 27, 2026, 9:01 p.m.
Created at: March 27, 2026, 3:04 p.m.