Triple

T27292976
Position Surface form Disambiguated ID Type / Status
Subject Hiroshima metropolitan area E688679 entity
Predicate majorCity P316 FINISHED
Object Ōno, Hatsukaichi
Ōno is a district within the city of Hatsukaichi in Hiroshima Prefecture, Japan, known as part of the urban area surrounding Hiroshima City.
E1069961 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: Ōno, Hatsukaichi | Statement: [Hiroshima metropolitan area, majorCity, Ōno, Hatsukaichi]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ōno, Hatsukaichi
Triple: [Hiroshima metropolitan area, majorCity, Ōno, Hatsukaichi]
Generated description
Ōno is a district within the city of Hatsukaichi in Hiroshima Prefecture, Japan, known as part of the urban area surrounding Hiroshima City.

Provenance (5 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_69ef355a96308190a2bed991525fb278 completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f6275afc848190a0b321716814673e completed May 2, 2026, 4:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12a7c8a77081908ebdb7d2f7344d7a completed May 24, 2026, 7:24 a.m.
NEDg Description generation batch_6a12a8f06dd4819082b919c0eaf0195d completed May 24, 2026, 7:29 a.m.
NED2 Entity disambiguation (via description) batch_6a12a9da3fa0819084049ed2e7bfbd79 completed May 24, 2026, 7:33 a.m.
Created at: April 27, 2026, 11:16 a.m.