Triple

T11819532
Position Surface form Disambiguated ID Type / Status
Subject 2000 Russian presidential election E281086 entity
Predicate incumbentBeforeOfficeStatus P6364 FINISHED
Object acting President of Russia 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: acting President of Russia | Statement: [2000 Russian presidential election, incumbentBeforeOfficeStatus, acting President of Russia]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: incumbentBeforeOfficeStatus
Context triple: [2000 Russian presidential election, incumbentBeforeOfficeStatus, acting President of Russia]
  • A. incumbentBeforeElection chosen
    Indicates that the subject was already holding the relevant office or position prior to the specified election.
  • B. lastIncumbent
    Indicates that the subject is the most recent person or entity to have held a particular position, office, or role before the current one.
  • C. incumbent
    Indicates that an entity currently holds a particular position, office, or role at the present time.
  • D. incumbentAfterElection
    Indicates that an entity holds a position or office as the sitting incumbent following a specified election.
  • E. precededByOfficeHolder
    Indicates that one office holder directly held a position before another office holder in a sequence of occupants of the same office.
  • 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_69d6ab26aae88190b2489efcb2a24234 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5e87e488190905bc3bb6d721e56 completed April 10, 2026, 7:25 a.m.
PD Predicate disambiguation batch_69d8a251fc08819095933f1d13c3b742 completed April 10, 2026, 7:10 a.m.
Created at: April 8, 2026, 9:42 p.m.