Triple

T35504072
Position Surface form Disambiguated ID Type / Status
Subject Spencer Bachus E1026092 entity
Predicate servedInCongressNumber P37694 FINISHED
Object 103rd United States Congress NE NERFINISHED

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: 103rd United States Congress | Statement: [Spencer Bachus, servedInCongressNumber, 103rd United States Congress]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: servedInCongressNumber
Context triple: [Spencer Bachus, servedInCongressNumber, 103rd United States Congress]
  • A. servedInCongress
    Indicates that an individual held an official legislative position as a member of a national congress during some period of time.
  • B. representedInCongressNumber chosen
    Indicates that an entity’s representation or service is associated with a specific numbered session of a legislative congress.
  • C. representedInCongressBy
    Indicates that one entity serves as the official congressional representative (e.g., legislator) for another entity (such as a person, group, or geographic area).
  • D. representedInCongressSince
    Indicates that an entity has served as a representative in a legislative congress continuously since a specified date or time.
  • E. numberOfTermsInCongress
    Indicates how many distinct terms an individual has served as a member of a legislative congress.
  • 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_69f76dfc9c60819089c4217d93922615 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_6a000fda03948190881b7275f249768f completed May 10, 2026, 4:55 a.m.
PD Predicate disambiguation batch_6a000f607f1881908ee750d58da91690 completed May 10, 2026, 4:53 a.m.
Created at: May 3, 2026, 4:04 p.m.