Triple

T4957882
Position Surface form Disambiguated ID Type / Status
Subject Yakushi-ji E111330 entity
Predicate hasStructure P35 FINISHED
Object Kondo
Kondo is the main hall of Yakushi-ji Temple in Nara, Japan, renowned for enshrining important Buddhist images and serving as the temple’s central worship space.
 E483064 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: Kondo | Statement: [Yakushi-ji, hasStructure, Kondo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kondo
Context triple: [Yakushi-ji, hasStructure, Kondo]
  • A. Takaichi
    Takaichi is a Japanese surname most prominently associated with conservative politician Sanae Takaichi.
  • B. Shuji
    Shuji is a Japanese given name most notably borne by Nobel Prize–winning physicist Shuji Nakamura.
  • C. Kentarō
    Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
  • D. Kenjirō
    Kenjirō is a Japanese masculine given name that can be written with various kanji combinations and is borne by multiple notable individuals in fields such as sports, arts, and entertainment.
  • E. Katsuya
    Katsuya is a Japanese given name commonly used for males.
  • 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: Kondo
Triple: [Yakushi-ji, hasStructure, Kondo]
Generated description
Kondo is the main hall of Yakushi-ji Temple in Nara, Japan, renowned for enshrining important Buddhist images and serving as the temple’s central worship space.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kondo
Target entity description: Kondo is the main hall of Yakushi-ji Temple in Nara, Japan, renowned for enshrining important Buddhist images and serving as the temple’s central worship space.
  • A. Takaichi
    Takaichi is a Japanese surname most prominently associated with conservative politician Sanae Takaichi.
  • B. Shuji
    Shuji is a Japanese given name most notably borne by Nobel Prize–winning physicist Shuji Nakamura.
  • C. Kentarō
    Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
  • D. Kenjirō
    Kenjirō is a Japanese masculine given name that can be written with various kanji combinations and is borne by multiple notable individuals in fields such as sports, arts, and entertainment.
  • E. Katsuya
    Katsuya is a Japanese given name commonly used for males.
  • 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_69bd4418390c8190b7e9766a2512ce55 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd71d834c0819087f3faafdc9b4228 completed March 20, 2026, 4:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69be81e144a08190b66bf07e09b6ff55 completed March 21, 2026, 11:32 a.m.
NEDg Description generation batch_69be83b10e048190889289ac2ca9f07f completed March 21, 2026, 11:40 a.m.
NED2 Entity disambiguation (via description) batch_69be843e2e50819099b2b73498c7c16e completed March 21, 2026, 11:42 a.m.
Created at: March 20, 2026, 1:32 p.m.