Triple

T29488771
Position Surface form Disambiguated ID Type / Status
Subject Survivor: Cambodia E748009 entity
Predicate preJuryReturneesCount P166965 FINISHED
Object 10 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: 10 | Statement: [Survivor: Cambodia, preJuryReturneesCount, 10]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: preJuryReturneesCount
Context triple: [Survivor: Cambodia, preJuryReturneesCount, 10]
  • A. hasNumberOfJurors
    Indicates the relationship specifying how many jurors are associated with a given legal case, trial, or proceeding.
  • B. jurorNumber
    Indicates the specific numerical identifier assigned to a juror within a jury.
  • C. hasJurors
    Indicates that one entity serves as or includes jurors in relation to another entity, typically in the context of a legal case or proceeding.
  • D. hasJuror
    Indicates that a person or legal body is assigned or associated with a specific juror in a judicial context.
  • E. hasSubJuries
    Indicates that an entity (typically a main jury or committee) is composed of or associated with one or more subordinate juries.
  • F. None of above. chosen

Provenance (4 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_69f0bd43ba30819095eb1cfc3adf525c completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66c08d734819088f227ef5b054acb completed May 2, 2026, 9:26 p.m.
PD Predicate disambiguation batch_69f6633ac8a88190ab0cda62bbfcf9b0 completed May 2, 2026, 8:48 p.m.
PDg Predicate description generation batch_69f6642e676c8190af0e6b1416eed6d2 completed May 2, 2026, 8:53 p.m.
Created at: April 28, 2026, 4:11 p.m.