Triple

T19986602
Position Surface form Disambiguated ID Type / Status
Subject Anup Kumar E493947 entity
Predicate startedProfessionalCareer P89592 FINISHED
Object with Central Reserve Police Force kabaddi team 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: with Central Reserve Police Force kabaddi team | Statement: [Anup Kumar, startedProfessionalCareer, with Central Reserve Police Force kabaddi team]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: startedProfessionalCareer
Context triple: [Anup Kumar, startedProfessionalCareer, with Central Reserve Police Force kabaddi team]
  • A. startedCareerWith chosen
    Indicates that an entity began its professional career associated with, employed by, or active for another specified entity.
  • B. startTimeOfProfessionalCareer
    Indicates the point in time when an individual’s professional career formally begins.
  • C. startedSoloCareer
    Indicates that an individual began pursuing a professional career independently, separate from any previous group or collaborative affiliation.
  • D. launchedCareerOf
    Indicates that one entity’s actions, support, or involvement initiated or significantly advanced another entity’s professional career.
  • E. startedStandUpCareerIn
    Indicates that an individual began their stand-up comedy career in a particular place 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_69da626a67648190af9653832a3aeced completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e65d16f60c81909ba02c0a3429ecae completed April 20, 2026, 5:06 p.m.
PD Predicate disambiguation batch_69e537fd311881908448f2aea8b4812e completed April 19, 2026, 8:15 p.m.
Created at: April 11, 2026, 3:29 p.m.