Triple

T21997519
Position Surface form Disambiguated ID Type / Status
Subject CSAT (General Studies Paper II) E543243 entity
Predicate qualifyingMarksRequirement P22279 FINISHED
Object 33 percent 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: 33 percent | Statement: [CSAT (General Studies Paper II), qualifyingMarksRequirement, 33 percent]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: qualifyingMarksRequirement
Context triple: [CSAT (General Studies Paper II), qualifyingMarksRequirement, 33 percent]
  • A. requiresMinimumScore chosen
    Indicates that one entity can only be obtained, accessed, or considered valid if another entity’s score meets or exceeds a specified minimum threshold.
  • B. qualifyingFor
    Indicates that one entity meets the necessary conditions or criteria to be eligible for another entity, status, or action.
  • C. hasQualification
    Indicates that an entity possesses a specific qualification, credential, or competency.
  • D. requiresQualificationStandard
    Indicates that performing or engaging in the referenced activity, role, or process is contingent upon meeting a specified qualification standard.
  • E. hasQualificationCriteria
    Indicates that there are specific conditions or standards that must be met for something to be considered eligible or acceptable.
  • 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_69e11e2c814c8190837d072789000486 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1276774508190b96870266e10979a completed April 28, 2026, 9:32 p.m.
PD Predicate disambiguation batch_69e6f62dc9d88190ae387f145f9528de completed April 21, 2026, 3:59 a.m.
Created at: April 16, 2026, 8:19 p.m.