Triple

T1595903
Position Surface form Disambiguated ID Type / Status
Subject Shiga E34281 entity
Predicate hasCity P316 FINISHED
Object Ōtsu E384443 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: Ōtsu | Statement: [Shiga, hasCity, Ōtsu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ōtsu
Context triple: [Shiga, hasCity, Ōtsu]
  • A. Ōtsu chosen
    Ōtsu is a Japanese city on the southwestern shore of Lake Biwa, known for its historic temples, scenic lake views, and role as a transportation hub near Kyoto.
  • B. Kaizuka
    Kaizuka is a coastal city in Osaka Prefecture, Japan, known for its historical temples, traditional festivals, and proximity to Osaka Bay.
  • C. Kishiwada
    Kishiwada is a coastal city in southern Osaka Prefecture, Japan, best known for its historic castle and the lively Kishiwada Danjiri Matsuri festival.
  • D. Neyagawa
    Neyagawa is a city in Osaka Prefecture, Japan, known as a residential and commercial suburb within the Osaka metropolitan area.
  • E. Hikone
    Hikone is a historic city in Shiga Prefecture, Japan, best known for its well-preserved Hikone Castle overlooking Lake Biwa.
  • 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_69a885fdcb9c819081ce6f0b8cd477dd completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9092ccb388190b2f3ed86b3853651 completed March 5, 2026, 4:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69b4e4b980888190a7df10662789f61e completed March 14, 2026, 4:31 a.m.
Created at: March 4, 2026, 7:27 p.m.