Triple

T16264155
Position Surface form Disambiguated ID Type / Status
Subject Temple 75: Zentsūji E394830 entity
Predicate hasSubcomplex P25619 FINISHED
Object Tō-in
Tō-in is a subcomplex of the historic Zentsūji Temple on the Shikoku Pilgrimage, known for its religious structures and role in the temple’s broader sacred precinct.
 E1207647 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: Tō-in | Statement: [Temple 75: Zentsūji, hasSubcomplex, Tō-in]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tō-in
Context triple: [Temple 75: Zentsūji, hasSubcomplex, Tō-in]
  • A. Takayoshi
    Takayoshi is a Japanese given name notably borne by Kido Takayoshi, a key samurai and statesman of the Meiji Restoration.
  • B. Shinshiro
    Shinshiro is a city in eastern Aichi Prefecture, Japan, known for its mountainous scenery, historic battle sites, and traditional rural landscapes.
  • C. Tokuji
    Tokuji is a Japanese masculine given name that has been borne by various notable individuals in fields such as business, politics, and the arts.
  • D. Hokuzan
    Hokuzan was a medieval kingdom in northern Okinawa that existed before the unification of the Ryukyu Islands under the Ryukyu Kingdom.
  • E. Seishirō
    Seishirō is a Japanese given name commonly used for male individuals.
  • 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: Tō-in
Triple: [Temple 75: Zentsūji, hasSubcomplex, Tō-in]
Generated description
Tō-in is a subcomplex of the historic Zentsūji Temple on the Shikoku Pilgrimage, known for its religious structures and role in the temple’s broader sacred precinct.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tō-in
Target entity description: Tō-in is a subcomplex of the historic Zentsūji Temple on the Shikoku Pilgrimage, known for its religious structures and role in the temple’s broader sacred precinct.
  • A. Takayoshi
    Takayoshi is a Japanese given name notably borne by Kido Takayoshi, a key samurai and statesman of the Meiji Restoration.
  • B. Shinshiro
    Shinshiro is a city in eastern Aichi Prefecture, Japan, known for its mountainous scenery, historic battle sites, and traditional rural landscapes.
  • C. Tokuji
    Tokuji is a Japanese masculine given name that has been borne by various notable individuals in fields such as business, politics, and the arts.
  • D. Hokuzan
    Hokuzan was a medieval kingdom in northern Okinawa that existed before the unification of the Ryukyu Islands under the Ryukyu Kingdom.
  • E. Seishirō
    Seishirō is a Japanese given name commonly used for male individuals.
  • 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_69d87f221d8081909b0b2063e7528ba2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e245c672248190a4261be4696d52c5 completed April 17, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0025f9b8bc81909315b14c3c1f6d83 completed May 10, 2026, 6:30 a.m.
NEDg Description generation batch_6a002a0baf4881908b66001a3dfc85e2 completed May 10, 2026, 6:47 a.m.
NED2 Entity disambiguation (via description) batch_6a002a63eca08190a6280466475044a5 completed May 10, 2026, 6:49 a.m.
Created at: April 10, 2026, 5:05 a.m.