Triple

T38386461
Position Surface form Disambiguated ID Type / Status
Subject Iya Valley E899591 entity
Predicate hasRoad P959 FINISHED
Object National Route 32
National Route 32 is a major Japanese highway on Shikoku that connects Kagawa and Kōchi Prefectures, running through scenic areas such as the Iya Valley.
 E2286158 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 32 | Statement: [Iya Valley, hasRoad, National Route 32]
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 32
Triple: [Iya Valley, hasRoad, National Route 32]
Generated description
National Route 32 is a major Japanese highway on Shikoku that connects Kagawa and Kōchi Prefectures, running through scenic areas such as the Iya Valley.

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_69f76e5c9b808190b486523f5c2f817d completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69fccd1cd7dc8190aee796392cda089a completed May 7, 2026, 5:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a464f1c36288190a0d6373f6b3bff4a completed July 2, 2026, 11:44 a.m.
NEDg Description generation batch_6a464feae5a08190ab244199838161ec completed July 2, 2026, 11:47 a.m.
NED2 Entity disambiguation (via description) batch_6a4650f219788190945e7fdafd043cc9 completed July 2, 2026, 11:52 a.m.
Created at: May 3, 2026, 4:31 p.m.