Triple

T32044170
Position Surface form Disambiguated ID Type / Status
Subject Kawaramachi Station E818293 entity
Predicate locatedUnder P10157 FINISHED
Object Shijō Street
Shijō Street is one of Kyoto’s main commercial and shopping thoroughfares, running east–west through the city and lined with department stores, boutiques, and entertainment venues.
 E2002340 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: Shijō Street | Statement: [Kawaramachi Station, locatedUnder, Shijō Street]
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: Shijō Street
Triple: [Kawaramachi Station, locatedUnder, Shijō Street]
Generated description
Shijō Street is one of Kyoto’s main commercial and shopping thoroughfares, running east–west through the city and lined with department stores, boutiques, and entertainment venues.

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_69f348fcfb648190859f6be5e04b7cfe completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b4c05ba481908cef2571dcfe1ea4 completed May 3, 2026, 2:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3056e7af788190b93e991fb206e961 completed June 15, 2026, 7:47 p.m.
NEDg Description generation batch_6a31b0156b30819095927096a6205842 completed June 16, 2026, 8:20 p.m.
NED2 Entity disambiguation (via description) batch_6a31b17557e88190b6c66d1f8a37ae13 completed June 16, 2026, 8:26 p.m.
Created at: May 1, 2026, 12:20 a.m.