Triple

T4928067
Position Surface form Disambiguated ID Type / Status
Subject Sook Ching massacre E110624 entity
Predicate officialDeathTollReportedByJapanese P59527 FINISHED
Object 5000 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: 5000 | Statement: [Sook Ching massacre, officialDeathTollReportedByJapanese, 5000]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: officialDeathTollReportedByJapanese
Context triple: [Sook Ching massacre, officialDeathTollReportedByJapanese, 5000]
  • A. casualtiesJapanKilled
    Indicates that the casualties were individuals from Japan who were killed.
  • B. casualtiesJapan
    Indicates that an event or action resulted in casualties (deaths and/or injuries) occurring in Japan.
  • C. JapaneseCasualtiesWounded
    Indicates that the relationship specifies the number of Japanese individuals who were wounded (but not killed) as casualties in a particular event or context.
  • D. nativeCasualties
    Indicates that native or indigenous people suffered deaths or injuries as a result of a particular event, action, or conflict.
  • E. militaryCasualtiesEstimate
    Indicates an estimated number of people killed, wounded, or missing as a result of military conflict or operations.
  • 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_69bd4415190c8190817bee7ec9f9f944 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd7036d8e88190bc4be2975160da23 completed March 20, 2026, 4:05 p.m.
PD Predicate disambiguation batch_69bd6c3695c8819094e7ad2f6d4ba1ac completed March 20, 2026, 3:48 p.m.
PDg Predicate description generation batch_69bd6d3806f881909c06687e9e57b67f completed March 20, 2026, 3:52 p.m.
Created at: March 20, 2026, 1:30 p.m.