Triple

T2532388
Position Surface form Disambiguated ID Type / Status
Subject Kyobashi Station E56190 entity
Predicate hasStationCode P1289 FINISHED
Object JR-H41
JR-H41 is the JR West station code assigned to Kyobashi Station on the Osaka Loop Line in Osaka, Japan.
 E275027 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: JR-H41 | Statement: [Kyobashi Station, hasStationCode, JR-H41]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: JR-H41
Context triple: [Kyobashi Station, hasStationCode, JR-H41]
  • A. JR-O11
    JR-O11 is the station code assigned to Osaka Station on the JR West railway network in Japan.
  • B. JR-O06
    JR-O06 is the station code assigned to Osakajokoen Station on the JR West railway network in Osaka, Japan.
  • C. J80
    J80 is the internal chassis code used by Toyota for the 80-series Land Cruiser platform that underpins the first-generation Lexus LX luxury SUV.
  • D. JR
    JR is a French street artist and photographer renowned for his large-scale public art installations that transform urban spaces and address social and political issues worldwide.
  • E. J100
    J100 is the internal model code used by Lexus to designate the second generation of its full-size luxury SUV, the Lexus LX.
  • 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: JR-H41
Triple: [Kyobashi Station, hasStationCode, JR-H41]
Generated description
JR-H41 is the JR West station code assigned to Kyobashi Station on the Osaka Loop Line in Osaka, Japan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: JR-H41
Target entity description: JR-H41 is the JR West station code assigned to Kyobashi Station on the Osaka Loop Line in Osaka, Japan.
  • A. JR-O11
    JR-O11 is the station code assigned to Osaka Station on the JR West railway network in Japan.
  • B. JR-O06
    JR-O06 is the station code assigned to Osakajokoen Station on the JR West railway network in Osaka, Japan.
  • C. J80
    J80 is the internal chassis code used by Toyota for the 80-series Land Cruiser platform that underpins the first-generation Lexus LX luxury SUV.
  • D. JR
    JR is a French street artist and photographer renowned for his large-scale public art installations that transform urban spaces and address social and political issues worldwide.
  • E. J100
    J100 is the internal model code used by Lexus to designate the second generation of its full-size luxury SUV, the Lexus LX.
  • 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_69ab4a49b6508190bc467fbef4bac334 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd279cf108190b03fb6e0265f39d9 completed March 7, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69af2bb9c37081909128d7a227651c8b completed March 9, 2026, 8:21 p.m.
NEDg Description generation batch_69af4fedb0a48190a9d9da8eeebfe074 completed March 9, 2026, 10:55 p.m.
NED2 Entity disambiguation (via description) batch_69af50551fd88190829d20ab2be426d4 completed March 9, 2026, 10:57 p.m.
Created at: March 6, 2026, 9:47 p.m.