Triple

T5960207
Position Surface form Disambiguated ID Type / Status
Subject Tobu 9000 series E132615 entity
Predicate depot P14646 FINISHED
Object Shiki Depot
Shiki Depot is a Tobu Railway maintenance and storage facility that services and houses Tobu 9000 series commuter trains.
 E558115 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: Shiki Depot | Statement: [Tobu 9000 series, depot, Shiki Depot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shiki Depot
Context triple: [Tobu 9000 series, depot, Shiki Depot]
  • A. Suminoe Depot
    Suminoe Depot is a railway maintenance and storage facility serving Osaka Metro’s Yotsubashi Line in Osaka, Japan.
  • B. Kasukabe Depot
    Kasukabe Depot is a railway maintenance and storage facility in Kasukabe, Saitama Prefecture, serving Tokyo Metro’s subway rolling stock.
  • C. Morinomiya Depot
    Morinomiya Depot is a major Osaka Metro facility used for the storage, inspection, and maintenance of trains serving the Sennichimae Line and other routes.
  • D. Nakamozu Depot
    Nakamozu Depot is a major rail yard and maintenance facility serving Osaka Metro’s Midosuji Line in Osaka, Japan.
  • E. Saginuma Depot
    Saginuma Depot is a maintenance and storage facility for Tokyo Metro trains serving the Hanzomon Line in the Tokyo area.
  • 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: Shiki Depot
Triple: [Tobu 9000 series, depot, Shiki Depot]
Generated description
Shiki Depot is a Tobu Railway maintenance and storage facility that services and houses Tobu 9000 series commuter trains.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Shiki Depot
Target entity description: Shiki Depot is a Tobu Railway maintenance and storage facility that services and houses Tobu 9000 series commuter trains.
  • A. Suminoe Depot
    Suminoe Depot is a railway maintenance and storage facility serving Osaka Metro’s Yotsubashi Line in Osaka, Japan.
  • B. Kasukabe Depot
    Kasukabe Depot is a railway maintenance and storage facility in Kasukabe, Saitama Prefecture, serving Tokyo Metro’s subway rolling stock.
  • C. Morinomiya Depot
    Morinomiya Depot is a major Osaka Metro facility used for the storage, inspection, and maintenance of trains serving the Sennichimae Line and other routes.
  • D. Nakamozu Depot
    Nakamozu Depot is a major rail yard and maintenance facility serving Osaka Metro’s Midosuji Line in Osaka, Japan.
  • E. Saginuma Depot
    Saginuma Depot is a maintenance and storage facility for Tokyo Metro trains serving the Hanzomon Line in the Tokyo area.
  • 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_69c0086c2364819091e9fe2f58fa2517 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c039fd6dd48190a6020bef38b1be82 completed March 22, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e3e8f234819099336503a797e55b completed March 23, 2026, 6:55 a.m.
NEDg Description generation batch_69c0ebb1dcb88190a101d3c88c647b41 completed March 23, 2026, 7:28 a.m.
NED2 Entity disambiguation (via description) batch_69c0ec4d1da081909cc6320078db4e53 completed March 23, 2026, 7:31 a.m.
Created at: March 22, 2026, 4:02 p.m.