Triple

T35639580
Position Surface form Disambiguated ID Type / Status
Subject 道央自動車道 E1029819 entity
Predicate hasInterchange P3495 FINISHED
Object 北広島IC
北広島ICは、北海道北広島市に位置し札幌近郊へのアクセス拠点となっている道央自動車道のインターチェンジである。
 E2149678 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: 北広島IC | Statement: [道央自動車道, hasInterchange, 北広島IC]
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: 北広島IC
Triple: [道央自動車道, hasInterchange, 北広島IC]
Generated description
北広島ICは、北海道北広島市に位置し札幌近郊へのアクセス拠点となっている道央自動車道のインターチェンジである。

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_69f76e087bdc8190a4794bf9c0bd7634 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79f4ab48c8190988340c0ee825ffa completed May 3, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3868549bf881908cb0a9b196f0eed9 completed June 21, 2026, 10:40 p.m.
NEDg Description generation batch_6a3869e1926c8190bd04917c34792658 completed June 21, 2026, 10:46 p.m.
NED2 Entity disambiguation (via description) batch_6a386a43d1508190984bac73f91988cd completed June 21, 2026, 10:48 p.m.
Created at: May 3, 2026, 4:05 p.m.