Triple

T17009803
Position Surface form Disambiguated ID Type / Status
Subject Jiyugaoka Station E412667 entity
Predicate hasStationCode P1289 FINISHED
Object TY07
TY07 is the station code assigned to Jiyugaoka Station on Tokyo’s Tokyu railway network.
E1244620 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: TY07 | Statement: [Jiyugaoka Station, hasStationCode, TY07]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TY07
Context triple: [Jiyugaoka Station, hasStationCode, TY07]
  • A. TYO:7012
    TYO:7012 is the Tokyo Stock Exchange ticker symbol for Kawasaki Heavy Industries, a major Japanese manufacturer of transportation equipment, industrial machinery, and aerospace products.
  • B. TX-07
    TX-07 is a United States congressional district located in the Houston area of Texas, represented in the U.S. House of Representatives.
  • C. TYO:6752
    TYO:6752 is the Tokyo Stock Exchange ticker symbol for Panasonic Corporation, a major Japanese multinational electronics and home appliances manufacturer.
  • D. PH-07
    PH-07 is the ISO 3166-2 code assigned to the Central Visayas administrative region of the Philippines.
  • E. J70
    The J70 is a long-running generation of the Toyota Land Cruiser renowned for its rugged body-on-frame construction, off-road durability, and continued use in demanding commercial and remote-area applications worldwide.
  • 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: TY07
Triple: [Jiyugaoka Station, hasStationCode, TY07]
Generated description
TY07 is the station code assigned to Jiyugaoka Station on Tokyo’s Tokyu railway network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: TY07
Target entity description: TY07 is the station code assigned to Jiyugaoka Station on Tokyo’s Tokyu railway network.
  • A. TYO:7012
    TYO:7012 is the Tokyo Stock Exchange ticker symbol for Kawasaki Heavy Industries, a major Japanese manufacturer of transportation equipment, industrial machinery, and aerospace products.
  • B. TX-07
    TX-07 is a United States congressional district located in the Houston area of Texas, represented in the U.S. House of Representatives.
  • C. TYO:6752
    TYO:6752 is the Tokyo Stock Exchange ticker symbol for Panasonic Corporation, a major Japanese multinational electronics and home appliances manufacturer.
  • D. PH-07
    PH-07 is the ISO 3166-2 code assigned to the Central Visayas administrative region of the Philippines.
  • E. J70
    The J70 is a long-running generation of the Toyota Land Cruiser renowned for its rugged body-on-frame construction, off-road durability, and continued use in demanding commercial and remote-area applications worldwide.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d47a8444819081f1262eb7dbda40 completed April 18, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc241ec88190a3e868ab88b26f09 completed May 10, 2026, 7:27 p.m.
NEDg Description generation batch_6a0114d7d03c8190943777f4eac956fd completed May 10, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a01159a08b081908fc82adc7cca532a completed May 10, 2026, 11:32 p.m.
Created at: April 10, 2026, 5:33 a.m.