Triple

T27904732
Position Surface form Disambiguated ID Type / Status
Subject Domyoji Station E705735 entity
Predicate railwayLine P848 FINISHED
Object Kintetsu Domyoji Line
The Kintetsu Domyoji Line is a short commuter railway line in Osaka Prefecture, Japan, operated by Kintetsu Railway and connecting Domyoji Station with nearby local destinations.
E2050736 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: Kintetsu Domyoji Line | Statement: [Domyoji Station, railwayLine, Kintetsu Domyoji 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: Kintetsu Domyoji Line
Triple: [Domyoji Station, railwayLine, Kintetsu Domyoji Line]
Generated description
The Kintetsu Domyoji Line is a short commuter railway line in Osaka Prefecture, Japan, operated by Kintetsu Railway and connecting Domyoji Station with nearby local destinations.

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_69ef96b5aad08190be36a277c31e7004 completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69f639fc02148190b67402ee8c312000 completed May 2, 2026, 5:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a35812c24e8819080bfd65027a52b88 completed June 19, 2026, 5:49 p.m.
NEDg Description generation batch_6a35820972dc81908d3854fd2eae1288 completed June 19, 2026, 5:53 p.m.
NED2 Entity disambiguation (via description) batch_6a35828addb4819094e945cfbf65b72a completed June 19, 2026, 5:55 p.m.
Created at: April 27, 2026, 6:44 p.m.