Triple

T32985435
Position Surface form Disambiguated ID Type / Status
Subject National Route 23 E843927 entity
Predicate hasJunctionWith P1018 FINISHED
Object National Route 25
National Route 25 is a major Japanese national highway that serves as an important east–west corridor connecting cities in the Kansai region.
 E2223271 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 25 | Statement: [National Route 23, hasJunctionWith, National Route 25]
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 25
Triple: [National Route 23, hasJunctionWith, National Route 25]
Generated description
National Route 25 is a major Japanese national highway that serves as an important east–west corridor connecting cities in the Kansai region.

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_69f3494c6f9c8190a255409fce8b1d3b completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d1df503c81908891d658ed0ed09c completed May 3, 2026, 4:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a406cb47048819096c51142ec6deee5 completed June 28, 2026, 12:37 a.m.
NEDg Description generation batch_6a406db565b881909769124848e2b508 completed June 28, 2026, 12:41 a.m.
NED2 Entity disambiguation (via description) batch_6a406e2e5e00819097b90719f08951c8 completed June 28, 2026, 12:43 a.m.
Created at: May 1, 2026, 1:22 a.m.