Triple

T11567040
Position Surface form Disambiguated ID Type / Status
Subject Atsugi E274278 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Ebina E812534 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: Ebina | Statement: [Atsugi, neighboringMunicipality, Ebina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ebina
Context triple: [Atsugi, neighboringMunicipality, Ebina]
  • A. Ebina chosen
    Ebina is a city in central Kanagawa Prefecture, Japan, known as a residential and commercial hub with convenient access to the Tokyo metropolitan area.
  • B. Shibukawa
    Shibukawa is a city in Gunma Prefecture, Japan, known as a regional transport hub and gateway to nearby hot spring resorts such as Ikaho Onsen.
  • C. Maishima
    Maishima is a man-made island in Osaka, Japan, known for its sports facilities, event venues, and waterfront recreational areas.
  • D. Higashikawa
    Higashikawa is a town in Hokkaido, Japan, known as a gateway to the Daisetsuzan mountain range and for its scenic natural landscapes.
  • E. Ayabe
    Ayabe is a small city in the northern part of Japan’s Kyoto Prefecture, known for its rural landscapes, traditional industries, and spiritual retreat centers.
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88dd4305c8190ac5ff490b6b63e12 completed April 10, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6af38e3548190a5192894932d9b1d completed May 3, 2026, 2:13 a.m.
Created at: April 8, 2026, 9:37 p.m.