Triple

T1603413
Position Surface form Disambiguated ID Type / Status
Subject Tokyo Tower E34445 entity
Predicate neighborhood P988 FINISHED
Object Shiba-koen
Shiba-koen is a central Tokyo district known for its large public park, historic temples, and close proximity to Tokyo Tower.
 E198513 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: Shiba-koen | Statement: [Tokyo Tower, neighborhood, Shiba-koen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shiba-koen
Context triple: [Tokyo Tower, neighborhood, Shiba-koen]
  • A. Kitanomaru Park
    Kitanomaru Park is a public park in central Tokyo known for its historic grounds, museums, and tranquil green spaces adjacent to the Tokyo Imperial Palace.
  • B. Shukugawa Park
    Shukugawa Park is a scenic riverside park in Nishinomiya, Japan, renowned for its cherry blossom-lined paths and seasonal beauty.
  • C. Ueno
    Ueno is a major district in Tokyo known for Ueno Park, its museums, zoo, and busy transportation hub.
  • D. Miyashita Park
    Miyashita Park is a redeveloped urban park and shopping complex in Shibuya that combines green space, sports facilities, and commercial areas atop a multi-story building.
  • E. Kasumigaseki
    Kasumigaseki is a central district in Tokyo known as Japan’s main government and bureaucratic hub, housing numerous national ministries and agencies.
  • 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: Shiba-koen
Triple: [Tokyo Tower, neighborhood, Shiba-koen]
Generated description
Shiba-koen is a central Tokyo district known for its large public park, historic temples, and close proximity to Tokyo Tower.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Shiba-koen
Target entity description: Shiba-koen is a central Tokyo district known for its large public park, historic temples, and close proximity to Tokyo Tower.
  • A. Kitanomaru Park
    Kitanomaru Park is a public park in central Tokyo known for its historic grounds, museums, and tranquil green spaces adjacent to the Tokyo Imperial Palace.
  • B. Shukugawa Park
    Shukugawa Park is a scenic riverside park in Nishinomiya, Japan, renowned for its cherry blossom-lined paths and seasonal beauty.
  • C. Ueno
    Ueno is a major district in Tokyo known for Ueno Park, its museums, zoo, and busy transportation hub.
  • D. Miyashita Park
    Miyashita Park is a redeveloped urban park and shopping complex in Shibuya that combines green space, sports facilities, and commercial areas atop a multi-story building.
  • E. Kasumigaseki
    Kasumigaseki is a central district in Tokyo known as Japan’s main government and bureaucratic hub, housing numerous national ministries and agencies.
  • 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_69a885fea6a481909fe83ba6441f1774 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9094f96ec819090286c21b3dfddd5 completed March 5, 2026, 4:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada96dc52c8190be0ace80c5eb4cf3 completed March 8, 2026, 4:53 p.m.
NEDg Description generation batch_69adaab1fb6881908e0711ae1b69e2e5 completed March 8, 2026, 4:58 p.m.
NED2 Entity disambiguation (via description) batch_69adae9fdd3081908b1d9d7335cab1bd completed March 8, 2026, 5:15 p.m.
Created at: March 4, 2026, 7:28 p.m.