Triple

T9987321
Position Surface form Disambiguated ID Type / Status
Subject St. Bridget’s Convent, Colombo E196799 entity
Predicate hasAlumnaWhoHeldOffice P60895 FINISHED
Object Prime Minister of Sri Lanka 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: Prime Minister of Sri Lanka | Statement: [St. Bridget’s Convent, Colombo, hasAlumnaWhoHeldOffice, Prime Minister of Sri Lanka]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasAlumnaWhoHeldOffice
Context triple: [St. Bridget’s Convent, Colombo, hasAlumnaWhoHeldOffice, Prime Minister of Sri Lanka]
  • A. notableAlumnaOccupation
    Indicates that the occupation specified is the professional role or career for a person who is a notable alumna of a particular institution.
  • B. notableAlumnaRole chosen
    Indicates that a person, as a notable alumna, holds or has held a specific role or position associated with her alumni status.
  • C. hasFirstFemaleGraduate
    Indicates that an institution or program has a specific person who is recognized as its first female graduate.
  • D. hasHistoricalOfficeHolder
    Indicates that an office, position, or role has been held by a specific person at some point in the past.
  • E. isFirstFemaleHolderOfOffice
    Indicates that a person is the first woman ever to hold a particular office or position.
  • 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_69ca82f1678c819093d06320a05f16a4 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdc79c8b80819091dc16ac8fd0c720 completed April 2, 2026, 1:34 a.m.
PD Predicate disambiguation batch_69cd1da07db88190945bcdab3ca82e71 completed April 1, 2026, 1:29 p.m.
Created at: March 30, 2026, 8:50 p.m.