Triple

T5599689
Position Surface form Disambiguated ID Type / Status
Subject 神戸大学 E147086 entity
Predicate locatedIn P40 FINISHED
Object 神戸市
神戸市は、兵庫県の県庁所在地であり、国際貿易港や異国情緒あふれる街並みで知られる日本有数の港湾都市です。
 E580770 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: 神戸市 | Statement: [神戸大学, locatedIn, 神戸市]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 神戸市
Context triple: [神戸大学, locatedIn, 神戸市]
  • A. Osaka
    Osaka is Japan's third-largest city and a major economic, cultural, and historical hub known for its vibrant street food, bustling nightlife, and role as a commercial center in the Kansai region.
  • B. Higashiōsaka
    Higashiōsaka is an industrial and residential city in Japan known for its manufacturing base and location within the Osaka metropolitan area.
  • C. Kitakyushu
    Kitakyushu is a major industrial and port city located in Fukuoka Prefecture on Japan’s Kyushu island.
  • D. Kurashiki
    Kurashiki is a historic industrial and canal city in Okayama Prefecture, Japan, known for its well-preserved Edo-period merchant quarter and traditional warehouses.
  • E. Toyohashi
    Toyohashi is a city in Aichi Prefecture, Japan, known as a regional commercial and transportation hub on the Pacific coast of central Honshu.
  • 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: 神戸市
Triple: [神戸大学, locatedIn, 神戸市]
Generated description
神戸市は、兵庫県の県庁所在地であり、国際貿易港や異国情緒あふれる街並みで知られる日本有数の港湾都市です。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 神戸市
Target entity description: 神戸市は、兵庫県の県庁所在地であり、国際貿易港や異国情緒あふれる街並みで知られる日本有数の港湾都市です。
  • A. Osaka
    Osaka is Japan's third-largest city and a major economic, cultural, and historical hub known for its vibrant street food, bustling nightlife, and role as a commercial center in the Kansai region.
  • B. Higashiōsaka
    Higashiōsaka is an industrial and residential city in Japan known for its manufacturing base and location within the Osaka metropolitan area.
  • C. Kitakyushu
    Kitakyushu is a major industrial and port city located in Fukuoka Prefecture on Japan’s Kyushu island.
  • D. Kurashiki
    Kurashiki is a historic industrial and canal city in Okayama Prefecture, Japan, known for its well-preserved Edo-period merchant quarter and traditional warehouses.
  • E. Toyohashi
    Toyohashi is a city in Aichi Prefecture, Japan, known as a regional commercial and transportation hub on the Pacific coast of central Honshu.
  • 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_69c009043d648190a7af89698ccf1e3e completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020d936dc8190a2e599f1df9fdd91 completed March 22, 2026, 5:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69c24381aff48190980ada94ee95593e completed March 24, 2026, 7:55 a.m.
NEDg Description generation batch_69c4fb66b8e8819090524d1ef12688a7 completed March 26, 2026, 9:24 a.m.
NED2 Entity disambiguation (via description) batch_69c4fc3065bc81908d95fbd3d4655c76 completed March 26, 2026, 9:28 a.m.
Created at: March 22, 2026, 3:38 p.m.