Triple

T9894957
Position Surface form Disambiguated ID Type / Status
Subject Virginia Minor women’s suffrage case E181546 entity
Predicate plaintiffCitizenshipStatus P50609 FINISHED
Object U.S. citizen 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: U.S. citizen | Statement: [Virginia Minor women’s suffrage case, plaintiffCitizenshipStatus, U.S. citizen]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: plaintiffCitizenshipStatus
Context triple: [Virginia Minor women’s suffrage case, plaintiffCitizenshipStatus, U.S. citizen]
  • A. definedCitizenship
    Indicates that a formal citizenship status has been legally established or specified for an entity.
  • B. citizenshipType chosen
    Indicates the specific legal category or status of an individual's citizenship in relation to a state or country.
  • C. appliesToCitizenshipStatus
    Indicates that something (such as a rule, benefit, restriction, or condition) is relevant to or governs individuals based on their citizenship status.
  • D. citizenshipStatusVariesByTerritory
    Indicates that the rules or conditions of citizenship differ depending on the specific territory or jurisdiction involved.
  • E. dualCitizenshipStatus
    Indicates that an entity holds legal citizenship in two different countries simultaneously.
  • 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_69ca8283a6708190801af7a25a7ebb9f completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cdb4a89e148190901753e67483d72c completed April 2, 2026, 12:13 a.m.
PD Predicate disambiguation batch_69cd1d872d50819096b7ab166a8decf1 completed April 1, 2026, 1:28 p.m.
Created at: March 30, 2026, 8:39 p.m.