Triple

T13851384
Position Surface form Disambiguated ID Type / Status
Subject Toyokawa Navy Arsenal E332949 entity
Predicate locatedIn P40 FINISHED
Object Toyokawa 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: Toyokawa | Statement: [Toyokawa Navy Arsenal, locatedIn, Toyokawa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toyokawa
Context triple: [Toyokawa Navy Arsenal, locatedIn, Toyokawa]
  • A. Toyokawa chosen
    Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
  • B. Yawata
    Yawata is a city in Japan known for its historic Iwashimizu Hachimangū Shrine and its location in the southern part of Kyoto Prefecture.
  • C. Ichinoseki
    Ichinoseki is a city in northeastern Japan known as a gateway to the scenic and historic sites of southern Iwate Prefecture.
  • D. Tsuruga
    Tsuruga is a coastal city in Fukui Prefecture, Japan, known as a key port and transportation hub on the Sea of Japan side of Honshu.
  • 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 (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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02d8fb788190baef7537be2baecb completed April 14, 2026, 9:03 a.m.
Created at: April 9, 2026, 10:14 p.m.