Triple

T16101635
Position Surface form Disambiguated ID Type / Status
Subject Barbara Grutter E390633 entity
Predicate lawsuitSubject P83607 FINISHED
Object affirmative action in higher education admissions 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: affirmative action in higher education admissions | Statement: [Barbara Grutter, lawsuitSubject, affirmative action in higher education admissions]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: lawsuitSubject
Context triple: [Barbara Grutter, lawsuitSubject, affirmative action in higher education admissions]
  • A. legalDisputeSubject chosen
    Indicates that a legal dispute concerns, involves, or is specifically about the referenced subject or matter.
  • B. subjectOfLaw
    Indicates that a law, legal document, or legal provision is about, concerns, or applies to the referenced subject.
  • C. litigationType
    Indicates the specific category or nature of a legal dispute or court case associated with an entity or event.
  • D. legalCase
    Indicates a relationship where a formal legal dispute or proceeding exists between parties, typically adjudicated by a court or similar authority.
  • E. legalSubject
    Indicates that an entity is the bearer of legal rights, duties, or responsibilities within a legal relationship or context.
  • 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_69d87f198bc48190a8b7e53ca15b7ead completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1ff68686481909517eed4266729ca completed April 17, 2026, 9:37 a.m.
PD Predicate disambiguation batch_69e182804208819087f35307cd6e4103 completed April 17, 2026, 12:44 a.m.
Created at: April 10, 2026, 5 a.m.