Triple

T36257049
Position Surface form Disambiguated ID Type / Status
Subject UST Manila E891966 entity
Predicate alumniNotability P184820 FINISHED
Object has many influential alumni in politics, law, medicine, arts, and the Church 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: has many influential alumni in politics, law, medicine, arts, and the Church | Statement: [UST Manila, alumniNotability, has many influential alumni in politics, law, medicine, arts, and the Church]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: alumniNotability
Context triple: [UST Manila, alumniNotability, has many influential alumni in politics, law, medicine, arts, and the Church]
  • A. motherNotability
    Indicates that an entity’s mother is notable or has significant recognition or prominence.
  • B. organNotability
    Indicates that an organ is notable or significant in some specific context or for a particular purpose.
  • C. coachNotability
    Indicates that an individual is notable or distinguished specifically in their role as a coach.
  • D. DarbyFieldNotability
    Indicates that the subject’s primary notability or significance is associated with Darby Field.
  • E. designerNotability
    Indicates that an entity is notable or recognized specifically for its work or role as a designer.
  • 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_69f76e4599108190811532e707d6bc2c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b5fece288190bd538ba5391d45e7 completed May 3, 2026, 8:54 p.m.
PD Predicate disambiguation batch_69f7b4c44390819084fb5558b354658f completed May 3, 2026, 8:49 p.m.
PDg Predicate description generation batch_69f7b57aa0848190a22c31c3ff90e0ab completed May 3, 2026, 8:52 p.m.
Created at: May 3, 2026, 4:09 p.m.