Triple

T28200815
Position Surface form Disambiguated ID Type / Status
Subject Chita Peninsula E716877 entity
Predicate roadServedBy P385 FINISHED
Object National Route 155
National Route 155 is a Japanese national highway that connects and provides access to key cities and transport hubs around the Chita Peninsula in Aichi Prefecture.
 E1837319 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 155 | Statement: [Chita Peninsula, roadServedBy, National Route 155]
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 155
Triple: [Chita Peninsula, roadServedBy, National Route 155]
Generated description
National Route 155 is a Japanese national highway that connects and provides access to key cities and transport hubs around the Chita Peninsula in Aichi Prefecture.

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_69efd6b826908190857e6e7dad74ed93 completed April 27, 2026, 9:35 p.m.
NER Named-entity recognition batch_69f642d510548190b9f34ed50d80f858 completed May 2, 2026, 6:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24bb7c00ac8190a85b81584f1889c6 completed June 7, 2026, 12:29 a.m.
NEDg Description generation batch_6a24bff1b4c08190a75bde811f817760 completed June 7, 2026, 12:48 a.m.
NED2 Entity disambiguation (via description) batch_6a24caecac048190a5ea1ce35c7eca81 completed June 7, 2026, 1:35 a.m.
Created at: April 27, 2026, 10:31 p.m.