Triple

T10086301
Position Surface form Disambiguated ID Type / Status
Subject Liberian general election, 2011 E215229 entity
Predicate resultCharacterizationByObservers P70548 FINISHED
Object generally free and fair 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: generally free and fair | Statement: [Liberian general election, 2011, resultCharacterizationByObservers, generally free and fair]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: resultCharacterizationByObservers
Context triple: [Liberian general election, 2011, resultCharacterizationByObservers, generally free and fair]
  • A. resultCharacterization chosen
    Indicates how the outcome of an event, process, or action is qualitatively described or characterized.
  • B. scopeCharacterization
    Indicates how the extent, boundaries, or coverage of something is defined, described, or qualified in relation to another entity or context.
  • C. responseCharacterization
    Indicates how a given response is evaluated or described in terms of its qualities, attributes, or type.
  • D. ruleCharacterization
    Indicates that one rule is described, defined, or characterized in terms of another rule or set of rules.
  • E. observedResult
    Indicates that an entity has recorded or perceived a particular outcome, effect, or measurement resulting from some process or event.
  • 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_69ca83a1eed081908b2e9580f2ebeea7 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd04745b48190a77c422eb76b6660 completed April 2, 2026, 2:11 a.m.
PD Predicate disambiguation batch_69cd4b97870481908f7a89df10d58a9e completed April 1, 2026, 4:45 p.m.
Created at: March 30, 2026, 9:01 p.m.