Triple

T30351827
Position Surface form Disambiguated ID Type / Status
Subject Osaka City Museum of Fine Arts E772014 entity
Predicate publicTransitAccess P1288 FINISHED
Object Osaka Metro Tennoji Station
Osaka Metro Tennoji Station is a major subway hub in Osaka’s Tennoji district, providing convenient access to nearby cultural, commercial, and transportation facilities.
E1925644 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: Osaka Metro Tennoji Station | Statement: [Osaka City Museum of Fine Arts, publicTransitAccess, Osaka Metro Tennoji 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: Osaka Metro Tennoji Station
Triple: [Osaka City Museum of Fine Arts, publicTransitAccess, Osaka Metro Tennoji Station]
Generated description
Osaka Metro Tennoji Station is a major subway hub in Osaka’s Tennoji district, providing convenient access to nearby cultural, commercial, and transportation facilities.

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_69f2248c6f5c8190a6177842bf791a3c completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6823af4a4819095c725800c2be63e completed May 2, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2870cf52c88190a04805514ac29ca7 completed June 9, 2026, 8 p.m.
NEDg Description generation batch_6a2871f0ad448190a25e2cae7dada3b2 completed June 9, 2026, 8:05 p.m.
NED2 Entity disambiguation (via description) batch_6a28725d5f5881908b3936e27ccad2fc completed June 9, 2026, 8:06 p.m.
Created at: April 29, 2026, 7:56 p.m.