Triple

T21394446
Position Surface form Disambiguated ID Type / Status
Subject Kozan-ji E527742 entity
Predicate locatedIn P40 FINISHED
Object Ukyo-ku
Ukyo-ku is one of the wards of Kyoto, Japan, known for its historic temples, scenic mountains, and traditional cultural sites on the city’s western side.
E1488870 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: Ukyo-ku | Statement: [Kozan-ji, locatedIn, Ukyo-ku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ukyo-ku
Context triple: [Kozan-ji, locatedIn, Ukyo-ku]
  • A. Kokurakita-ku
    Kokurakita-ku is a central ward of Kitakyushu, Japan, known as a major commercial and administrative hub of the city.
  • B. Naniwa-ku
    Naniwa-ku is a central ward of Osaka, Japan, known for its bustling entertainment districts, shopping streets, and iconic landmarks such as Tsutenkaku Tower.
  • C. Nishinari-ku
    Nishinari-ku is a ward in Osaka, Japan, known for its dense urban environment, working-class neighborhoods, and historically being one of the city's poorest districts.
  • D. Aoi-ku
    Aoi-ku is a central ward of Shizuoka City in Japan, known for housing the city’s main administrative and commercial districts.
  • E. Taihaku-ku
    Taihaku-ku is a ward in the city of Sendai, Japan, known for its mix of residential areas, natural scenery, and hot spring resorts.
  • 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: Ukyo-ku
Triple: [Kozan-ji, locatedIn, Ukyo-ku]
Generated description
Ukyo-ku is one of the wards of Kyoto, Japan, known for its historic temples, scenic mountains, and traditional cultural sites on the city’s western side.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ukyo-ku
Target entity description: Ukyo-ku is one of the wards of Kyoto, Japan, known for its historic temples, scenic mountains, and traditional cultural sites on the city’s western side.
  • A. Kokurakita-ku
    Kokurakita-ku is a central ward of Kitakyushu, Japan, known as a major commercial and administrative hub of the city.
  • B. Naniwa-ku
    Naniwa-ku is a central ward of Osaka, Japan, known for its bustling entertainment districts, shopping streets, and iconic landmarks such as Tsutenkaku Tower.
  • C. Nishinari-ku
    Nishinari-ku is a ward in Osaka, Japan, known for its dense urban environment, working-class neighborhoods, and historically being one of the city's poorest districts.
  • D. Aoi-ku
    Aoi-ku is a central ward of Shizuoka City in Japan, known for housing the city’s main administrative and commercial districts.
  • E. Taihaku-ku
    Taihaku-ku is a ward in the city of Sendai, Japan, known for its mix of residential areas, natural scenery, and hot spring resorts.
  • 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_69e0b51ff3748190935c0a513c62a12b completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69ee62cd30f08190aba90afed6116a2a completed April 26, 2026, 7:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a09e8120484819096566a1ab353e78c completed May 17, 2026, 4:08 p.m.
NEDg Description generation batch_6a09e939e31c8190a6bae24ac06250e7 completed May 17, 2026, 4:13 p.m.
NED2 Entity disambiguation (via description) batch_6a09e9cf75308190a2878f6ab0b5f5a2 completed May 17, 2026, 4:16 p.m.
Created at: April 16, 2026, 5:13 p.m.