Triple

T25265176
Position Surface form Disambiguated ID Type / Status
Subject British detention camps in Cyprus E633410 entity
Predicate numberOfDetainees P13732 FINISHED
Object over 50,000 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: over 50,000 | Statement: [British detention camps in Cyprus, numberOfDetainees, over 50,000]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: numberOfDetainees
Context triple: [British detention camps in Cyprus, numberOfDetainees, over 50,000]
  • A. detainedPopulation
    Indicates that a population of individuals is being held in custody or confinement, typically by legal or governmental authority.
  • B. coDetainee
    Indicates that two or more individuals are detained or imprisoned together in the same facility or under the same custodial authority.
  • C. estimatedPrisonerCount
    Indicates the estimated number of prisoners associated with a particular context, such as a location, time period, or event.
  • D. detainedPrisonersFrom
    Indicates that an authority is holding prisoners who originate from or are associated with a specified place or source.
  • E. numberOfPrisonersApproximate chosen
    Indicates an approximate count of prisoners associated with an entity or situation, rather than an exact number.
  • 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_69e75a922ad481908f4f1f884583cb42 completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f6ffbad8848190867c2988c0ceb84f completed May 3, 2026, 7:56 a.m.
PD Predicate disambiguation batch_69f6fc53f4f881908dcc698687bbb64d completed May 3, 2026, 7:42 a.m.
Created at: April 21, 2026, 1:14 p.m.