Triple

T26123297
Position Surface form Disambiguated ID Type / Status
Subject Ninomiya E659033 entity
Predicate governingBody P46 FINISHED
Object Ninomiya town government
Ninomiya town government is the local municipal authority responsible for administering public services, regulations, and community affairs in the town of Ninomiya.
E1712128 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: Ninomiya town government | Statement: [Ninomiya, governingBody, Ninomiya town government]
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: Ninomiya town government
Triple: [Ninomiya, governingBody, Ninomiya town government]
Generated description
Ninomiya town government is the local municipal authority responsible for administering public services, regulations, and community affairs in the town of Ninomiya.

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_69ee5bc2b2948190b458ad3f580af779 completed April 26, 2026, 6:38 p.m.
NER Named-entity recognition batch_69f60acd4cdc8190bbb11e4171c685b0 completed May 2, 2026, 2:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a112759ed788190bbf086bf2b1ffef3 completed May 23, 2026, 4:04 a.m.
NEDg Description generation batch_6a1152ca293c8190bb09fc8c8a22403a completed May 23, 2026, 7:10 a.m.
NED2 Entity disambiguation (via description) batch_6a1153247c388190807c81edacd9ea3e completed May 23, 2026, 7:11 a.m.
Created at: April 26, 2026, 8:10 p.m.