Triple

T25603151
Position Surface form Disambiguated ID Type / Status
Subject Equal Rights Amendment E641838 entity
Predicate languageTargets P178564 FINISHED
Object United States federal government 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: United States federal government | Statement: [Equal Rights Amendment, languageTargets, United States federal government]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: languageTargets
Context triple: [Equal Rights Amendment, languageTargets, United States federal government]
  • A. targetLanguage
    Indicates the language that is the intended recipient or focus of a communication, translation, or linguistic operation.
  • B. languageProvision
    Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
  • C. languageCategory
    Indicates the classification relationship where a language is assigned to a particular linguistic or functional category.
  • D. languagePair
    Indicates a relationship that associates two specific languages as a paired combination, typically for translation, comparison, or mapping between them.
  • E. languageBranch
    Indicates that one language belongs to, or is classified under, a broader linguistic branch or subgroup.
  • F. None of above. chosen

Provenance (4 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_69e75dc6ccf081908d49578fd36a76d5 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f7117e55908190a67105e92bc4830f completed May 3, 2026, 9:12 a.m.
PD Predicate disambiguation batch_69f70f380690819090cc34763ba460ed completed May 3, 2026, 9:02 a.m.
PDg Predicate description generation batch_69f7117cf2188190b29e36fc1e342c60 completed May 3, 2026, 9:12 a.m.
Created at: April 21, 2026, 4:36 p.m.