Triple

T16239774
Position Surface form Disambiguated ID Type / Status
Subject Maibara E394210 entity
Predicate hasJapaneseName P9882 FINISHED
Object 米原市
米原市は、滋賀県北東部に位置し、東海道新幹線や在来線が交差する交通の要衝として知られる市です。
 E1202251 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: 米原市 | Statement: [Maibara, hasJapaneseName, 米原市]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 米原市
Context triple: [Maibara, hasJapaneseName, 米原市]
  • A. 柏原市
    柏原市は、大阪府南東部に位置し、歴史ある寺社やぶどう栽培などで知られる中規模の都市です。
  • B. 川越市
    川越市 is a historic city in Saitama Prefecture, Japan, famed for its well-preserved Edo-period streetscapes and traditional warehouse-style buildings that have earned it the nickname "Little Edo."
  • C. 丹波市
    丹波市 is a rural city in central Hyōgo Prefecture, Japan, known for its historic castle town atmosphere, agricultural products, and scenic natural landscapes.
  • D. 福知山市
    福知山市 is a city in northern Kyoto Prefecture, Japan, known as a regional commercial and transportation hub with a mix of historical sites and rural landscapes.
  • E. 津山市
    津山市 is a historic castle town and regional city in Okayama Prefecture, Japan, known for Tsuyama Castle ruins and its preserved traditional streetscapes.
  • 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: 米原市
Triple: [Maibara, hasJapaneseName, 米原市]
Generated description
米原市は、滋賀県北東部に位置し、東海道新幹線や在来線が交差する交通の要衝として知られる市です。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 米原市
Target entity description: 米原市は、滋賀県北東部に位置し、東海道新幹線や在来線が交差する交通の要衝として知られる市です。
  • A. 柏原市
    柏原市は、大阪府南東部に位置し、歴史ある寺社やぶどう栽培などで知られる中規模の都市です。
  • B. 川越市
    川越市 is a historic city in Saitama Prefecture, Japan, famed for its well-preserved Edo-period streetscapes and traditional warehouse-style buildings that have earned it the nickname "Little Edo."
  • C. 丹波市
    丹波市 is a rural city in central Hyōgo Prefecture, Japan, known for its historic castle town atmosphere, agricultural products, and scenic natural landscapes.
  • D. 福知山市
    福知山市 is a city in northern Kyoto Prefecture, Japan, known as a regional commercial and transportation hub with a mix of historical sites and rural landscapes.
  • E. 津山市
    津山市 is a historic castle town and regional city in Okayama Prefecture, Japan, known for Tsuyama Castle ruins and its preserved traditional streetscapes.
  • 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_69d87f2171208190951025e526947816 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2455d5270819090171d4207223a28 completed April 17, 2026, 2:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a000edd1ed08190aa0211c3b17a918e completed May 10, 2026, 4:51 a.m.
NEDg Description generation batch_6a00108fdda88190bf510d04f4cc73f1 completed May 10, 2026, 4:58 a.m.
NED2 Entity disambiguation (via description) batch_6a0011559b748190ad406263889514a4 completed May 10, 2026, 5:02 a.m.
Created at: April 10, 2026, 5:04 a.m.