Triple

T22533399
Position Surface form Disambiguated ID Type / Status
Subject 東京都港区 E557098 entity
Predicate containsStation P83367 FINISHED
Object 広尾駅
広尾駅は、東京都港区の高級住宅街と大使館が集まるエリアに位置する東京メトロ日比谷線の地下鉄駅です。
 E1662206 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: 広尾駅 | Statement: [東京都港区, containsStation, 広尾駅]
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: 広尾駅
Triple: [東京都港区, containsStation, 広尾駅]
Generated description
広尾駅は、東京都港区の高級住宅街と大使館が集まるエリアに位置する東京メトロ日比谷線の地下鉄駅です。

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_69e11e57483c8190b0887c4f8ff26446 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15ed88cf08190ae7e5b6bf9a80372 completed April 29, 2026, 1:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10485e968c8190a4d2bc48d346d2b9 completed May 22, 2026, 12:13 p.m.
NEDg Description generation batch_6a1049f04c5c819091dc7e9d760c91ce completed May 22, 2026, 12:20 p.m.
NED2 Entity disambiguation (via description) batch_6a104bc7449081909da91b61b68319af completed May 22, 2026, 12:27 p.m.
Created at: April 16, 2026, 8:51 p.m.