Triple

T8354644
Position Surface form Disambiguated ID Type / Status
Subject 中部地方 E196653 entity
Predicate hasMajorCity P316 FINISHED
Object 富山市
富山市は、日本の本州中央部に位置し、立山連峰や富山湾に囲まれた自然景観と工業・商業が発達した富山県の県庁所在地の都市です。
E727572 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: 富山市 | Statement: [中部地方, hasMajorCity, 富山市]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 富山市
Context triple: [中部地方, hasMajorCity, 富山市]
  • A. 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.
  • B. 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.
  • C. 岐阜市
    岐阜市 is the capital city of Gifu Prefecture in central Japan, known as a regional commercial hub with historical ties to samurai-era Gifu Castle and traditional cormorant fishing on the Nagara River.
  • D. 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."
  • E. 木津川市
    木津川市は、京都府南部に位置し、奈良県に隣接する住宅都市・歴史観光地として発展している市です。
  • 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: 富山市
Triple: [中部地方, hasMajorCity, 富山市]
Generated description
富山市は、日本の本州中央部に位置し、立山連峰や富山湾に囲まれた自然景観と工業・商業が発達した富山県の県庁所在地の都市です。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 富山市
Target entity description: 富山市は、日本の本州中央部に位置し、立山連峰や富山湾に囲まれた自然景観と工業・商業が発達した富山県の県庁所在地の都市です。
  • A. 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.
  • B. 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.
  • C. 岐阜市
    岐阜市 is the capital city of Gifu Prefecture in central Japan, known as a regional commercial hub with historical ties to samurai-era Gifu Castle and traditional cormorant fishing on the Nagara River.
  • D. 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."
  • E. 木津川市
    木津川市は、京都府南部に位置し、奈良県に隣接する住宅都市・歴史観光地として発展している市です。
  • 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_69ca82f08b348190bfb7881944bbff6f completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb8048edb88190a1980ad74818b898 completed March 31, 2026, 8:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc75e94288190ba1905dd4ca172dd completed April 2, 2026, 1:33 a.m.
NEDg Description generation batch_69cdcc86626c8190a4206feedea24b41 completed April 2, 2026, 1:55 a.m.
NED2 Entity disambiguation (via description) batch_69cdcde02e088190be8220f7d18d6700 completed April 2, 2026, 2:01 a.m.
Created at: March 30, 2026, 5:59 p.m.