Triple

T13633159
Position Surface form Disambiguated ID Type / Status
Subject 京阪本線 E325776 entity
Predicate 主要駅 P1071 FINISHED
Object 祇園四条駅
祇園四条駅は、京都市東山区の祇園エリアに位置し、観光や繁華街へのアクセス拠点となっている京阪電鉄の主要駅です。
E1050877 NE FINISHED

How this triple was built (4 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: 祇園四条駅 | Statement: [京阪本線, 主要駅, 祇園四条駅]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 祇園四条駅
Context triple: [京阪本線, 主要駅, 祇園四条駅]
  • A. Higashiyama Station
    Higashiyama Station is an underground metro station in Kyoto, Japan, serving the Kyoto Municipal Subway network and providing access to the historic Higashiyama district.
  • B. 京阪黄檗駅
    京阪黄檗駅は、京都府宇治市に位置し、京阪電気鉄道宇治線が乗り入れる京都大学宇治キャンパス最寄りの鉄道駅です。
  • C. Shinsaibashi Station
    Shinsaibashi Station is a major Osaka Metro subway station in Osaka, Japan, serving as a key transit hub for the bustling Shinsaibashi shopping and entertainment district.
  • D. 嵯峨嵐山駅
    嵯峨嵐山駅 is a railway station in Kyoto, Japan, serving as a key access point for tourists visiting the scenic Arashiyama district.
  • E. 三軒茶屋駅
    三軒茶屋駅 is a major railway station in Tokyo’s Setagaya ward, serving as a key transit hub on the Tokyu Den-en-toshi and Setagaya Lines and a gateway to the lively Sangen-jaya neighborhood.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: 祇園四条駅
Triple: [京阪本線, 主要駅, 祇園四条駅]
Generated description
祇園四条駅は、京都市東山区の祇園エリアに位置し、観光や繁華街へのアクセス拠点となっている京阪電鉄の主要駅です。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 祇園四条駅
Target entity description: 祇園四条駅は、京都市東山区の祇園エリアに位置し、観光や繁華街へのアクセス拠点となっている京阪電鉄の主要駅です。
  • A. Higashiyama Station
    Higashiyama Station is an underground metro station in Kyoto, Japan, serving the Kyoto Municipal Subway network and providing access to the historic Higashiyama district.
  • B. 京阪黄檗駅
    京阪黄檗駅は、京都府宇治市に位置し、京阪電気鉄道宇治線が乗り入れる京都大学宇治キャンパス最寄りの鉄道駅です。
  • C. Shinsaibashi Station
    Shinsaibashi Station is a major Osaka Metro subway station in Osaka, Japan, serving as a key transit hub for the bustling Shinsaibashi shopping and entertainment district.
  • D. 嵯峨嵐山駅
    嵯峨嵐山駅 is a railway station in Kyoto, Japan, serving as a key access point for tourists visiting the scenic Arashiyama district.
  • E. 三軒茶屋駅
    三軒茶屋駅 is a major railway station in Tokyo’s Setagaya ward, serving as a key transit hub on the Tokyu Den-en-toshi and Setagaya Lines and a gateway to the lively Sangen-jaya neighborhood.
  • F. None of above. chosen

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_69d8076beddc8190a53156f5bea77f5e completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc5a490508190924ac40f1dd519d6 completed April 12, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77fab07648190b3b3362a8ffa8961 completed May 3, 2026, 5:02 p.m.
NEDg Description generation batch_69f78070e95c819088982e26fe2d8e26 completed May 3, 2026, 5:05 p.m.
NED2 Entity disambiguation (via description) batch_69f7815a858c8190a9ae47012d04f8e1 completed May 3, 2026, 5:09 p.m.
Created at: April 9, 2026, 9:51 p.m.