Triple

T21164764
Position Surface form Disambiguated ID Type / Status
Subject Shinano Railway Line E521529 entity
Predicate intermediateMajorStation P30882 FINISHED
Object Yashiro Station
Yashiro Station is a key passenger railway station in Chikuma, Nagano Prefecture, Japan, serving as an important stop on the Shinano Railway Line.
E2296847 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: Yashiro Station | Statement: [Shinano Railway Line, intermediateMajorStation, Yashiro 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: Yashiro Station
Triple: [Shinano Railway Line, intermediateMajorStation, Yashiro Station]
Generated description
Yashiro Station is a key passenger railway station in Chikuma, Nagano Prefecture, Japan, serving as an important stop on the Shinano Railway Line.

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_69e0b50e30748190b186824a206d39b9 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7270e15bc81908d609198e573040e completed April 21, 2026, 7:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a82c896a2b08190b556fc48973308bc completed Aug. 17, 2026, 8:38 a.m.
NEDg Description generation batch_6a82c8fd6a98819088d03b11b2d19cad completed Aug. 17, 2026, 8:40 a.m.
NED2 Entity disambiguation (via description) batch_6a82c95216c88190a5a31112eee431df completed Aug. 17, 2026, 8:41 a.m.
Created at: April 16, 2026, 2:59 p.m.