Triple

T25718665
Position Surface form Disambiguated ID Type / Status
Subject Saku City E644924 entity
Predicate roadServedBy P385 FINISHED
Object National Route 141
National Route 141 is a Japanese national highway in Nagano and Yamanashi Prefectures that connects inland cities such as Saku with the Kōfu area.
 E1706597 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: National Route 141 | Statement: [Saku City, roadServedBy, National Route 141]
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: National Route 141
Triple: [Saku City, roadServedBy, National Route 141]
Generated description
National Route 141 is a Japanese national highway in Nagano and Yamanashi Prefectures that connects inland cities such as Saku with the Kōfu area.

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_69e77e8476fc8190bd5e9d05b89fad0a completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5fc64597c8190bfd867fb93834195 completed May 2, 2026, 1:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a111aede3488190bd0352a13678a784 completed May 23, 2026, 3:11 a.m.
NEDg Description generation batch_6a111b8972c8819098e58a3403b7dec9 completed May 23, 2026, 3:14 a.m.
NED2 Entity disambiguation (via description) batch_6a111c84387481909caa6fbfbb38d855 completed May 23, 2026, 3:18 a.m.
Created at: April 21, 2026, 9:49 p.m.