Triple

T3101855
Position Surface form Disambiguated ID Type / Status
Subject Mittelbau-Dora concentration camp E64736 entity
Predicate prisonerPopulation P14018 FINISHED
Object tens of thousands of prisoners 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: tens of thousands of prisoners | Statement: [Mittelbau-Dora concentration camp, prisonerPopulation, tens of thousands of prisoners]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: prisonerPopulation
Context triple: [Mittelbau-Dora concentration camp, prisonerPopulation, tens of thousands of prisoners]
  • A. numberOfPrisonersApproximate
    Indicates an approximate count of prisoners associated with an entity or situation, rather than an exact number.
  • B. estimatedPrisonerCount chosen
    Indicates the estimated number of prisoners associated with a particular context, such as a location, time period, or event.
  • C. hasPrisonerPopulation
    Indicates that an entity maintains or contains a population of prisoners, specifying the number or presence of incarcerated individuals associated with it.
  • D. inmates
    Indicates that one entity is confined or held as a prisoner within an institution or facility associated with another entity.
  • E. estimatedPrisoners
    Indicates a relationship where a value represents the estimated number of prisoners associated with a particular entity or context.
  • 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_69ad857dc98481909e585dc3372e3ed5 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada26c76ec81908d11f82be573c518 completed March 8, 2026, 4:23 p.m.
PD Predicate disambiguation batch_69ad9df06ed88190809f0683122caa5a completed March 8, 2026, 4:04 p.m.
Created at: March 8, 2026, 3:03 p.m.