Triple

T38105604
Position Surface form Disambiguated ID Type / Status
Subject 右京区 E951500 entity
Predicate hasRailwayStation P918 FINISHED
Object 太秦駅
太秦駅は、京都市右京区に位置し、主に嵐電やJR線を利用する乗客のアクセス拠点となっている鉄道駅です。
 E2255657 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: 太秦駅 | Statement: [右京区, hasRailwayStation, 太秦駅]
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: 太秦駅
Triple: [右京区, hasRailwayStation, 太秦駅]
Generated description
太秦駅は、京都市右京区に位置し、主に嵐電やJR線を利用する乗客のアクセス拠点となっている鉄道駅です。

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_69f76f065ed08190bdfb1b6d817f5b39 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fc45a605b48190b3e6b3cb18164c2c completed May 7, 2026, 7:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a4168161e6c8190aa23b4127c6f492a completed June 28, 2026, 6:29 p.m.
NEDg Description generation batch_6a4168d9bee0819083592acaf9463302 completed June 28, 2026, 6:32 p.m.
NED2 Entity disambiguation (via description) batch_6a4169e703e0819096e9b39222f324da completed June 28, 2026, 6:37 p.m.
Created at: May 3, 2026, 4:21 p.m.