Triple

T38086813
Position Surface form Disambiguated ID Type / Status
Subject Rende District E950995 entity
Predicate isTraversedBy P416 FINISHED
Object Provincial Highway 86
Provincial Highway 86 is a major roadway in Taiwan that serves as an important east–west connector route, facilitating regional transportation and access across Tainan and surrounding areas.
E2256017 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: Provincial Highway 86 | Statement: [Rende District, isTraversedBy, Provincial Highway 86]
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: Provincial Highway 86
Triple: [Rende District, isTraversedBy, Provincial Highway 86]
Generated description
Provincial Highway 86 is a major roadway in Taiwan that serves as an important east–west connector route, facilitating regional transportation and access across Tainan and surrounding areas.

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_69f76f03a3608190a73fd6df87c792a8 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fc456f33048190a303b87c366a64c8 completed May 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a41680a4bf88190ad7d99e9afa2b668 completed June 28, 2026, 6:29 p.m.
NEDg Description generation batch_6a4169b2cf688190a6cb47420df591e3 completed June 28, 2026, 6:36 p.m.
NED2 Entity disambiguation (via description) batch_6a416b2d776c8190b5e206273ee3dc29 completed June 28, 2026, 6:42 p.m.
Created at: May 3, 2026, 4:21 p.m.