Triple

T32476216
Position Surface form Disambiguated ID Type / Status
Subject Spacia limited express E829982 entity
Predicate railwayLineUsed P848 FINISHED
Object Tobu Kinugawa Line
The Tobu Kinugawa Line is a Japanese railway line in Tochigi Prefecture operated by Tobu Railway, serving as a key route to the Kinugawa Onsen hot spring resort area.
E2296659 NE FINISHED

How this triple was built (2 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: Tobu Kinugawa Line | Statement: [Spacia limited express, railwayLineUsed, Tobu Kinugawa Line]
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: Tobu Kinugawa Line
Triple: [Spacia limited express, railwayLineUsed, Tobu Kinugawa Line]
Generated description
The Tobu Kinugawa Line is a Japanese railway line in Tochigi Prefecture operated by Tobu Railway, serving as a key route to the Kinugawa Onsen hot spring resort area.

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_69f3491ff3b48190b50a7fa00bb05b1f completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c3913f108190b2e10106534b6392 completed May 3, 2026, 3:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a829e17e0c481909f91489ac4013449 completed Aug. 17, 2026, 5:37 a.m.
NEDg Description generation batch_6a829e6945d08190ae56563bf419f409 completed Aug. 17, 2026, 5:38 a.m.
NED2 Entity disambiguation (via description) batch_6a829e9301d481908e93f97d3c00747c completed Aug. 17, 2026, 5:39 a.m.
Created at: May 1, 2026, 12:58 a.m.