Triple

T24832590
Position Surface form Disambiguated ID Type / Status
Subject Korea Expressway network E621379 entity
Predicate hasPart P35 FINISHED
Object Daegu–Busan Expressway
The Daegu–Busan Expressway is a major South Korean highway that provides a key high-speed road link between the inland city of Daegu and the coastal metropolis of Busan.
 E1699744 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: Daegu–Busan Expressway | Statement: [Korea Expressway network, hasPart, Daegu–Busan Expressway]
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: Daegu–Busan Expressway
Triple: [Korea Expressway network, hasPart, Daegu–Busan Expressway]
Generated description
The Daegu–Busan Expressway is a major South Korean highway that provides a key high-speed road link between the inland city of Daegu and the coastal metropolis of Busan.

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_69e2fac0c3b881909110e5a56c6fa46f completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f422b39bdc819098945c6e7b1a1a14 completed May 1, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10ec7bc1948190a5376d02eee4f5a3 completed May 22, 2026, 11:53 p.m.
NEDg Description generation batch_6a10ed7a51a481909346a6926eb90033 completed May 22, 2026, 11:57 p.m.
NED2 Entity disambiguation (via description) batch_6a10ee29be508190865fc3575aff7faa completed May 23, 2026, midnight
Created at: April 18, 2026, 5:16 a.m.