Triple

T36392838
Position Surface form Disambiguated ID Type / Status
Subject Ōsaka Namba Station E896374 entity
Predicate adjacentStation P5707 FINISHED
Object Hanshin Sakuragawa Station
Hanshin Sakuragawa Station is a railway station in Osaka, Japan, served by the Hanshin Namba Line and located near the city's central Namba district.
E2291963 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: Hanshin Sakuragawa Station | Statement: [Ōsaka Namba Station, adjacentStation, Hanshin Sakuragawa Station]
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: Hanshin Sakuragawa Station
Triple: [Ōsaka Namba Station, adjacentStation, Hanshin Sakuragawa Station]
Generated description
Hanshin Sakuragawa Station is a railway station in Osaka, Japan, served by the Hanshin Namba Line and located near the city's central Namba district.

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_69f76e52e3108190becf70b090ae7bd6 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bcda95e48190a7fb9e56b58233de completed May 3, 2026, 9:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5cab1cab008190a9e4d0e3b37a4536 completed July 19, 2026, 10:46 a.m.
NEDg Description generation batch_6a5cab7b40ec8190b5337d59b02a7251 completed July 19, 2026, 10:48 a.m.
NED2 Entity disambiguation (via description) batch_6a5cac002a4881908d09ca58aba1ba02 completed July 19, 2026, 10:50 a.m.
Created at: May 3, 2026, 4:10 p.m.