Triple

T20091311
Position Surface form Disambiguated ID Type / Status
Subject Izumisano Station E496274 entity
Predicate isKeyStopOn P3386 FINISHED
Object Nankai Airport Line
The Nankai Airport Line is a railway line in Osaka Prefecture, Japan, operated by Nankai Electric Railway that connects central Osaka with Kansai International Airport.
E434739 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: Nankai Airport Line | Statement: [Izumisano Station, isKeyStopOn, Nankai Airport 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: Nankai Airport Line
Triple: [Izumisano Station, isKeyStopOn, Nankai Airport Line]
Generated description
The Nankai Airport Line is a railway line in Osaka Prefecture, Japan, operated by Nankai Electric Railway that connects central Osaka with Kansai International Airport.

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_69da626eee3881909f3454986d4a6511 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6655edde08190a3f950e7f0c7cf9c completed April 20, 2026, 5:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a251f3b8b348190bb7398705055dcc1 completed June 7, 2026, 7:35 a.m.
NEDg Description generation batch_6a25233346e08190ae8ddd961a7a0aa6 completed June 7, 2026, 7:52 a.m.
NED2 Entity disambiguation (via description) batch_6a2524e8046c81908ce1d256c4efe3d5 completed June 7, 2026, 7:59 a.m.
Created at: April 11, 2026, 11:21 p.m.