Triple

T9640279
Position Surface form Disambiguated ID Type / Status
Subject Jintao E233044 entity
Predicate associatedWithPersonPosition P12885 FINISHED
Object President of the People's Republic of China 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: President of the People's Republic of China | Statement: [Jintao, associatedWithPersonPosition, President of the People's Republic of China]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedWithPersonPosition
Context triple: [Jintao, associatedWithPersonPosition, President of the People's Republic of China]
  • A. occupationOfAssociatedPerson
    Indicates the job or professional role held by a person who is associated with another referenced entity.
  • B. namedPersonRole chosen
    Indicates that a person is identified by name as holding a specific role or position in a given context.
  • C. personReferredToPosition
    Indicates that one entity has been mentioned or cited as a candidate or occupant for a particular role, job, or position.
  • D. associatedWithRank
    Indicates a relationship where an entity is linked to a specific rank, level, or hierarchical position.
  • E. isAssociatedWith
    Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
  • 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_69ca848a5a908190aad251f4137b0c3a completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9b552a1c81909a1fab347110eeb1 completed April 1, 2026, 10:25 p.m.
PD Predicate disambiguation batch_69ccd5b0263081908cf6df3eb07d71b0 completed April 1, 2026, 8:22 a.m.
Created at: March 30, 2026, 8:12 p.m.