Triple

T24832596
Position Surface form Disambiguated ID Type / Status
Subject Korea Expressway network E621379 entity
Predicate hasPart P35 FINISHED
Object Tongyeong–Daejeon Expressway
The Tongyeong–Daejeon Expressway is a major South Korean highway that connects the southern coastal city of Tongyeong with the inland metropolitan area of Daejeon, facilitating regional and national transportation.
E1720235 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: Tongyeong–Daejeon Expressway | Statement: [Korea Expressway network, hasPart, Tongyeong–Daejeon 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: Tongyeong–Daejeon Expressway
Triple: [Korea Expressway network, hasPart, Tongyeong–Daejeon Expressway]
Generated description
The Tongyeong–Daejeon Expressway is a major South Korean highway that connects the southern coastal city of Tongyeong with the inland metropolitan area of Daejeon, facilitating regional and national transportation.

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_6a119a15579c81908d9b373767f7fc08 completed May 23, 2026, 12:14 p.m.
NEDg Description generation batch_6a119abb744c8190be56b28fc5f9a642 completed May 23, 2026, 12:16 p.m.
NED2 Entity disambiguation (via description) batch_6a119b8de8e08190bcde7ef4efcf64a6 completed May 23, 2026, 12:20 p.m.
Created at: April 18, 2026, 5:16 a.m.