Triple

T17821671
Position Surface form Disambiguated ID Type / Status
Subject 千歳市 E444999 entity
Predicate 隣接自治体 P33892 FINISHED
Object 厚真町
厚真町は、北海道胆振総合振興局に属し、農業や畜産業を主産業とする自然豊かな町です。
 E1289980 NE FINISHED

How this triple was built (4 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: 厚真町 | Statement: [千歳市, 隣接自治体, 厚真町]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 厚真町
Context triple: [千歳市, 隣接自治体, 厚真町]
  • A. 永田町
    永田町 is a district in Tokyo’s Chiyoda Ward that serves as Japan’s political center, housing key government institutions and major party headquarters.
  • B. 厚木市
    厚木市 is a city in central Kanagawa Prefecture, Japan, known as a regional commercial and industrial center with convenient access to the Tokyo metropolitan area.
  • C. 瑞穂町
    瑞穂町は、日本の東京都西多摩郡に位置する住宅地と自然が混在する町です。
  • D. 太子町
    太子町は、聖徳太子ゆかりの史跡や寺院が点在することで知られる日本の町です。
  • E. 甲良町
    甲良町は、滋賀県犬上郡に位置する、歴史的な寺院や田園風景が広がる小規模な町です。
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: 厚真町
Triple: [千歳市, 隣接自治体, 厚真町]
Generated description
厚真町は、北海道胆振総合振興局に属し、農業や畜産業を主産業とする自然豊かな町です。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 厚真町
Target entity description: 厚真町は、北海道胆振総合振興局に属し、農業や畜産業を主産業とする自然豊かな町です。
  • A. 永田町
    永田町 is a district in Tokyo’s Chiyoda Ward that serves as Japan’s political center, housing key government institutions and major party headquarters.
  • B. 厚木市
    厚木市 is a city in central Kanagawa Prefecture, Japan, known as a regional commercial and industrial center with convenient access to the Tokyo metropolitan area.
  • C. 瑞穂町
    瑞穂町は、日本の東京都西多摩郡に位置する住宅地と自然が混在する町です。
  • D. 太子町
    太子町は、聖徳太子ゆかりの史跡や寺院が点在することで知られる日本の町です。
  • E. 甲良町
    甲良町は、滋賀県犬上郡に位置する、歴史的な寺院や田園風景が広がる小規模な町です。
  • F. None of above. chosen

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_69d8b9f0de78819099395b14db75a8a6 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48911b660819097fc7ea94665a02a completed April 19, 2026, 7:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a02ff680b548190b6f1fbc09335ff31 completed May 12, 2026, 10:22 a.m.
NEDg Description generation batch_6a0300ca1ac88190b474ac8276d55445 completed May 12, 2026, 10:28 a.m.
NED2 Entity disambiguation (via description) batch_6a03017f7ea08190b3a98db1c429d04f completed May 12, 2026, 10:31 a.m.
Created at: April 10, 2026, 10:15 a.m.