Triple

T27353745
Position Surface form Disambiguated ID Type / Status
Subject Stanley Internment Camp E685627 entity
Predicate hasApproximateNumberOfInternees P111137 FINISHED
Object about 3,000 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: about 3,000 | Statement: [Stanley Internment Camp, hasApproximateNumberOfInternees, about 3,000]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfInternees
Context triple: [Stanley Internment Camp, hasApproximateNumberOfInternees, about 3,000]
  • A. hasApproximateNumberOfResponsa
    Indicates that an entity is associated with a rough or estimated count of responsa, rather than an exact number.
  • B. hasApproximateNumberOfPeople chosen
    Indicates that an entity is associated with an estimated or approximate count of people, rather than an exact number.
  • C. approximateOccupation
    Indicates that one entity is inferred or estimated to be the occupation or job role of another entity, rather than being known with certainty.
  • D. hasApproximateStudents
    Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
  • E. hasMaximumNumberOfMembers
    Indicates that there is an upper limit on how many members can be associated with a given entity.
  • 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_69ef14887c288190931b8431fdbf53c4 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f707f7959881908f037f0d6b1d0c36 completed May 3, 2026, 8:31 a.m.
PD Predicate disambiguation batch_69f700fc274c8190a128593dc7c7abd0 completed May 3, 2026, 8:02 a.m.
Created at: April 27, 2026, 11:50 a.m.