Triple

T11805874
Position Surface form Disambiguated ID Type / Status
Subject Saitama Prefecture E280745 entity
Predicate hasMajorCity P316 FINISHED
Object Wako E188130 NE 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: Wako | Statement: [Saitama Prefecture, hasMajorCity, Wako]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wako
Context triple: [Saitama Prefecture, hasMajorCity, Wako]
  • A. Wako chosen
    Wako is a suburban city in Saitama Prefecture, Japan, located on the northern outskirts of Tokyo and known as a residential and commuter hub.
  • B. Owada
    Owada is a Japanese surname most notably borne by Empress Masako of Japan and her family.
  • C. Nishiwaki
    Nishiwaki is a city in central Hyōgo Prefecture, Japan, known for its location near the geographic center of the country and its mix of industrial and rural landscapes.
  • D. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • E. Warekena
    The Warekena are an Indigenous people of the Amazon region, primarily living along rivers in Brazil and Venezuela, known for their distinct Arawakan language and traditional riverine lifestyle.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d6ab26aae88190b2489efcb2a24234 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5c8324481909a54852a9bb714e0 completed April 10, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6f5b196bc8190a643f2b534497476 completed May 3, 2026, 7:13 a.m.
Created at: April 8, 2026, 9:42 p.m.