Triple

T15399702
Position Surface form Disambiguated ID Type / Status
Subject Daruma Market E368277 entity
Predicate hasLocalName P6353 FINISHED
Object だるま市
だるま市は、縁起物の達磨を売る露店が並び、商売繁盛や合格祈願などを願う人々で賑わう日本各地の伝統的な市や祭りの総称です。
E1154938 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: だるま市 | Statement: [Daruma Market, hasLocalName, だるま市]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: だるま市
Context triple: [Daruma Market, hasLocalName, だるま市]
  • A. Toda City
    Toda City is a municipality in Saitama Prefecture, Japan, located just north of Tokyo and known as a residential and commuter town within the Greater Tokyo metropolitan area.
  • B. Yuza Town
    Yuza Town is a coastal municipality in northern Japan known for its scenic location in Yamagata Prefecture near Mount Chōkai and the Sea of Japan.
  • C. Gotemba City
    Gotemba City is a Japanese city in Shizuoka Prefecture near the southeastern base of Mount Fuji, known as a gateway for climbing and tourism around the mountain.
  • D. Yamamoto Town
    Yamamoto Town is a coastal municipality in northeastern Japan known for agriculture and for being heavily affected by the 2011 Tōhoku earthquake and tsunami.
  • E. Nanyo City
    Nanyo City is a municipality in northeastern Japan known for its hot springs, fruit production, and scenic rural landscapes.
  • 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: だるま市
Triple: [Daruma Market, hasLocalName, だるま市]
Generated description
だるま市は、縁起物の達磨を売る露店が並び、商売繁盛や合格祈願などを願う人々で賑わう日本各地の伝統的な市や祭りの総称です。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: だるま市
Target entity description: だるま市は、縁起物の達磨を売る露店が並び、商売繁盛や合格祈願などを願う人々で賑わう日本各地の伝統的な市や祭りの総称です。
  • A. Toda City
    Toda City is a municipality in Saitama Prefecture, Japan, located just north of Tokyo and known as a residential and commuter town within the Greater Tokyo metropolitan area.
  • B. Yuza Town
    Yuza Town is a coastal municipality in northern Japan known for its scenic location in Yamagata Prefecture near Mount Chōkai and the Sea of Japan.
  • C. Gotemba City
    Gotemba City is a Japanese city in Shizuoka Prefecture near the southeastern base of Mount Fuji, known as a gateway for climbing and tourism around the mountain.
  • D. Yamamoto Town
    Yamamoto Town is a coastal municipality in northeastern Japan known for agriculture and for being heavily affected by the 2011 Tōhoku earthquake and tsunami.
  • E. Nanyo City
    Nanyo City is a municipality in northeastern Japan known for its hot springs, fruit production, and scenic rural landscapes.
  • 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_69d85a16c68c819099c1b547fbc87b32 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e8d89e08190b7cae778d89fb5e1 completed April 16, 2026, 1:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff13567e3481908eb6293c6af35f3a completed May 9, 2026, 10:58 a.m.
NEDg Description generation batch_69ff144af00481909191a2d33874c195 completed May 9, 2026, 11:02 a.m.
NED2 Entity disambiguation (via description) batch_69ff15ae7c9c81909fd0894e48e5b5b1 completed May 9, 2026, 11:08 a.m.
Created at: April 10, 2026, 3:19 a.m.