Triple

T8664689
Position Surface form Disambiguated ID Type / Status
Subject Okinawa City E205637 entity
Predicate adjacentTo P224 FINISHED
Object Uruma E208160 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: Uruma | Statement: [Okinawa City, adjacentTo, Uruma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uruma
Context triple: [Okinawa City, adjacentTo, Uruma]
  • A. Uruma chosen
    Uruma is a coastal city in central Okinawa, Japan, known for its scenic islands, historic sites, and U.S. military bases.
  • B. Nago
    Nago is a coastal city in northern Okinawa, Japan, known for its beaches, subtropical climate, and role as a regional commercial and cultural center.
  • C. Meerufenfushi
    Meerufenfushi is a small, picturesque resort island in the Maldives known for its white-sand beaches, clear turquoise waters, and overwater bungalows.
  • D. Yokadouma
    Yokadouma is a town in eastern Cameroon that serves as an important local administrative and commercial center near the country's forested border regions.
  • E. Takashima
    Takashima is a lakeside city in western Shiga Prefecture, Japan, known for its scenic location along Lake Biwa and surrounding mountains.
  • 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_69ca83516ae88190aefe034b3bc589e3 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc48a0ae108190b33dadcc3cb18949 completed March 31, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69cecd0d95ec81908669ee35f0987be7 completed April 2, 2026, 8:09 p.m.
Created at: March 30, 2026, 6:30 p.m.