Triple

T251735
Position Surface form Disambiguated ID Type / Status
Subject War Refugee Board E5162 entity
Predicate estimatedNumberOfPeopleSaved P8803 FINISHED
Object tens of thousands of Jews 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 Jews | Statement: [War Refugee Board, estimatedNumberOfPeopleSaved, tens of thousands of Jews]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: estimatedNumberOfPeopleSaved
Context triple: [War Refugee Board, estimatedNumberOfPeopleSaved, tens of thousands of Jews]
  • A. estimatedNumberOfSurvivorsAtLiberation
    Indicates the approximate count of individuals who were still alive at the time a camp or similar site was liberated.
  • B. casualtiesEstimate
    Indicates an estimated number of people killed, injured, or otherwise harmed as a result of an event or incident.
  • C. estimatedNumberEmancipated
    Indicates the estimated count of individuals who have been emancipated.
  • D. numberOfPeoplePressedToDeath
    Indicates the number of people who were killed specifically by being pressed to death.
  • E. supportedPopulation
    Indicates that one entity provides assistance, resources, or services to sustain or benefit a specified group of people.
  • 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_69a257c4bf688190a46ebbf411ab7473 completed Feb. 28, 2026, 2:49 a.m.
NER Named-entity recognition batch_69a25d39eb3881909f435043c8697f13 completed Feb. 28, 2026, 3:12 a.m.
PD Predicate disambiguation batch_69a25b678d6c81909780e1995c1ca691 completed Feb. 28, 2026, 3:05 a.m.
PDg Predicate description generation batch_69a25c2ca46c81908c61696f31e59a98 completed Feb. 28, 2026, 3:08 a.m.
Created at: Feb. 28, 2026, 2:54 a.m.