Triple

T21343501
Position Surface form Disambiguated ID Type / Status
Subject Tanimachi 4-chome Station E526263 entity
Predicate hasStationCode P1289 FINISHED
Object T23
T23 is the station code assigned to Tanimachi 4-chome Station on the Osaka Metro network in Japan.
 E1479301 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: T23 | Statement: [Tanimachi 4-chome Station, hasStationCode, T23]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: T23
Context triple: [Tanimachi 4-chome Station, hasStationCode, T23]
  • A. T-2
    T-2 is the Japanese Air Self-Defense Force designation for the Mitsubishi T-2, a supersonic jet trainer aircraft developed in Japan.
  • B. G23
    G23 is BMW’s internal model code for the second-generation 4 Series Convertible, a compact luxury drop-top introduced in the early 2020s.
  • C. T2
    T2 is one of the main lines of the Dijon tramway system in Dijon, France, providing urban light-rail transit service across the city.
  • D. T2
    T2 is a passenger terminal at Berlin Brandenburg Airport that handles check-in, security, and boarding operations for departing and arriving travelers.
  • E. T2
    T2 is the second passenger terminal at Chicago O'Hare International Airport, serving various domestic and regional airline operations.
  • 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: T23
Triple: [Tanimachi 4-chome Station, hasStationCode, T23]
Generated description
T23 is the station code assigned to Tanimachi 4-chome Station on the Osaka Metro network in Japan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: T23
Target entity description: T23 is the station code assigned to Tanimachi 4-chome Station on the Osaka Metro network in Japan.
  • A. T-2
    T-2 is the Japanese Air Self-Defense Force designation for the Mitsubishi T-2, a supersonic jet trainer aircraft developed in Japan.
  • B. G23
    G23 is BMW’s internal model code for the second-generation 4 Series Convertible, a compact luxury drop-top introduced in the early 2020s.
  • C. T2
    T2 is one of the main lines of the Dijon tramway system in Dijon, France, providing urban light-rail transit service across the city.
  • D. T2
    T2 is a passenger terminal at Berlin Brandenburg Airport that handles check-in, security, and boarding operations for departing and arriving travelers.
  • E. T2
    T2 is the second passenger terminal at Chicago O'Hare International Airport, serving various domestic and regional airline operations.
  • 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_69e0b51c33048190ab27cede74ef798c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8a8515bc48190b79f80e505550cd5 completed April 22, 2026, 10:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09a5c8c9808190810982de97320df3 completed May 17, 2026, 11:26 a.m.
NEDg Description generation batch_6a09a6848c1c8190992ae7cdfeabdcf8 completed May 17, 2026, 11:29 a.m.
NED2 Entity disambiguation (via description) batch_6a09aae23f2c81908f08d290277e22f9 completed May 17, 2026, 11:47 a.m.
Created at: April 16, 2026, 4:44 p.m.