Triple

T8397106
Position Surface form Disambiguated ID Type / Status
Subject Kita, Tokyo E198080 entity
Predicate hasResidentialArea P9064 FINISHED
Object Oji E666677 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: Oji | Statement: [Kita, Tokyo, hasResidentialArea, Oji]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oji
Context triple: [Kita, Tokyo, hasResidentialArea, Oji]
  • A. Oji chosen
    Oji is a town in Nara Prefecture, Japan, known as a residential and commercial hub within the Kansai region.
  • B. Oji River
    Oji River is a town and local government area in Enugu State, Nigeria, known historically for its coal deposits and power station.
  • C. Ogawa
    Ogawa is a town in Saitama Prefecture, Japan, known for its traditional Japanese paper (washi) production and its role as a local transport hub.
  • D. Ouakam
    Ouakam is a coastal district of Dakar, Senegal, known for its historic fishing community, military installations, and prominent location beneath the African Renaissance Monument.
  • E. Beni River
    The Beni River is a major waterway in northern Bolivia that flows through the Amazon Basin, supporting rich biodiversity and local communities along its course.
  • 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_69ca82f816bc8190ab321c07d72208c1 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb818893348190a6ea2ff6a2e3e491 completed March 31, 2026, 8:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde867d21c8190b066a6c88273ec5a completed April 2, 2026, 3:54 a.m.
Created at: March 30, 2026, 6:04 p.m.