Triple

T31072775
Position Surface form Disambiguated ID Type / Status
Subject Kurokawa Onsen E791867 entity
Predicate administrativeDistrict P2709 FINISHED
Object Aso District
Aso District is a rural administrative district in Kumamoto Prefecture, Japan, known for its hot spring resorts and proximity to the volcanic Aso region.
E2064178 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: Aso District | Statement: [Kurokawa Onsen, administrativeDistrict, Aso District]
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: Aso District
Triple: [Kurokawa Onsen, administrativeDistrict, Aso District]
Generated description
Aso District is a rural administrative district in Kumamoto Prefecture, Japan, known for its hot spring resorts and proximity to the volcanic Aso region.

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_69f224ccdbbc81909b0cdb4cc2d70c7a completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f695b7575c81909898124bfc346407 completed May 3, 2026, 12:24 a.m.
NED1 Entity disambiguation (via context triple) batch_6a363c6ce7008190bfb55fd1d158560e completed June 20, 2026, 7:08 a.m.
NEDg Description generation batch_6a3645b743b08190a35ecba58e3921e6 completed June 20, 2026, 7:48 a.m.
NED2 Entity disambiguation (via description) batch_6a3646364c248190b6b21b99d41667bc completed June 20, 2026, 7:50 a.m.
Created at: April 29, 2026, 9:01 p.m.