Triple

T14170333
Position Surface form Disambiguated ID Type / Status
Subject Nishihara, Okinawa E351188 entity
Predicate borders P224 FINISHED
Object Haebaru NE NERFINISHED

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: Haebaru | Statement: [Nishihara, Okinawa, borders, Haebaru]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haebaru
Context triple: [Nishihara, Okinawa, borders, Haebaru]
  • A. Haebaru chosen
    Haebaru is a town in Okinawa Prefecture, Japan, forming part of the greater Naha metropolitan area.
  • B. Aobayama
    Aobayama is a hilly, forested area in Sendai known for housing parts of Tohoku University and offering scenic views over the city.
  • C. Karasuwa
    Karasuwa is a local government area in northeastern Nigeria known for its predominantly rural communities and agricultural activities within Yobe State.
  • D. Niihama
    Niihama is an industrial city in western Japan known for its copper mining history and location along the Seto Inland Sea in Ehime Prefecture.
  • E. Shimaore
    Shimaore is a Bantu language closely related to Comorian, widely spoken by the local population of Mayotte in the Indian Ocean.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8278834a08190b0f1784e58d7b99c completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61b472288190b4a271daa54aa6cd completed April 14, 2026, 3:48 p.m.
Created at: April 10, 2026, 1:01 a.m.