Triple

T37060730
Position Surface form Disambiguated ID Type / Status
Subject 京都府京田辺市 E917315 entity
Predicate 主な駅 P30882 FINISHED
Object 新田辺駅
新田辺駅は、京都府京田辺市に位置し、近鉄京都線が乗り入れる同市の主要な鉄道ターミナル駅です。
E2213225 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: 新田辺駅 | Statement: [京都府京田辺市, 主な駅, 新田辺駅]
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: 新田辺駅
Triple: [京都府京田辺市, 主な駅, 新田辺駅]
Generated description
新田辺駅は、京都府京田辺市に位置し、近鉄京都線が乗り入れる同市の主要な鉄道ターミナル駅です。

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_69f76e95fa40819091e14681087ae5e4 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb2f6caa1c8190ae3f88df531481e4 completed May 6, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3efdba8da88190adc2fcd55be49c12 completed June 26, 2026, 10:31 p.m.
NEDg Description generation batch_6a3f4ec12e088190a4c5c53493e13826 completed June 27, 2026, 4:17 a.m.
NED2 Entity disambiguation (via description) batch_6a3f4f1cfa208190bd07ab6aee82fa6c completed June 27, 2026, 4:18 a.m.
Created at: May 3, 2026, 4:14 p.m.