Triple

T13041131
Position Surface form Disambiguated ID Type / Status
Subject Tōkai-Kanjō Expressway E327192 entity
Predicate connectsCity P4245 FINISHED
Object Inabe
Inabe is a city in Mie Prefecture, Japan, known for its rural landscapes, agriculture, and access to regional transport routes.
E1262159 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: Inabe | Statement: [Tōkai-Kanjō Expressway, connectsCity, Inabe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Inabe
Context triple: [Tōkai-Kanjō Expressway, connectsCity, Inabe]
  • A. Nakawa
    Nakawa is one of the energetic human hosts in Disney’s “Festival of the Lion King” stage show at Disney’s Animal Kingdom.
  • B. Aobayama
    Aobayama is a hilly, forested area in Sendai known for housing parts of Tohoku University and offering scenic views over the city.
  • C. Tatsuno
    Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
  • D. Nonoichi
    Nonoichi is a city in Ishikawa Prefecture, Japan, known for its residential character and proximity to the regional hub of Kanazawa.
  • E. Urakawa
    Urakawa is a coastal town in Hokkaido, Japan, known for its horse breeding industry and scenic Pacific shoreline.
  • 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: Inabe
Triple: [Tōkai-Kanjō Expressway, connectsCity, Inabe]
Generated description
Inabe is a city in Mie Prefecture, Japan, known for its rural landscapes, agriculture, and access to regional transport routes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Inabe
Target entity description: Inabe is a city in Mie Prefecture, Japan, known for its rural landscapes, agriculture, and access to regional transport routes.
  • A. Nakawa
    Nakawa is one of the energetic human hosts in Disney’s “Festival of the Lion King” stage show at Disney’s Animal Kingdom.
  • B. Aobayama
    Aobayama is a hilly, forested area in Sendai known for housing parts of Tohoku University and offering scenic views over the city.
  • C. Tatsuno
    Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
  • D. Nonoichi
    Nonoichi is a city in Ishikawa Prefecture, Japan, known for its residential character and proximity to the regional hub of Kanazawa.
  • E. Urakawa
    Urakawa is a coastal town in Hokkaido, Japan, known for its horse breeding industry and scenic Pacific shoreline.
  • 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_69d8076e64308190904fb5c93517c901 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d9804f0318819081516e2ca1de6797 completed April 10, 2026, 10:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0180bd1e5c8190a6a96581ce8a37de completed May 11, 2026, 7:09 a.m.
NEDg Description generation batch_6a01850f55788190ac9c3d3188514aed completed May 11, 2026, 7:28 a.m.
NED2 Entity disambiguation (via description) batch_6a018577996081909bd2b06fdbe7c2fa completed May 11, 2026, 7:29 a.m.
Created at: April 9, 2026, 8:56 p.m.