Triple

T25018798
Position Surface form Disambiguated ID Type / Status
Subject Seoul Ring Expressway E626214 entity
Predicate isNumberedAs P22578 FINISHED
Object National Expressway Route 100
National Expressway Route 100 is a major ring expressway encircling Seoul, South Korea, that helps divert traffic around the city and connect key regional routes.
 E1662428 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 Expressway Route 100 | Statement: [Seoul Ring Expressway, isNumberedAs, National Expressway Route 100]
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 Expressway Route 100
Triple: [Seoul Ring Expressway, isNumberedAs, National Expressway Route 100]
Generated description
National Expressway Route 100 is a major ring expressway encircling Seoul, South Korea, that helps divert traffic around the city and connect key regional routes.

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_69e2ff27755881908490178e83701160 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f44ba7f8dc81908b4e7659d95f99be completed May 1, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1048b2a5b48190a1c9816ff28fdbc8 completed May 22, 2026, 12:14 p.m.
NEDg Description generation batch_6a10496ad0748190b797fea89fc9472d completed May 22, 2026, 12:17 p.m.
NED2 Entity disambiguation (via description) batch_6a104bc667e48190bb0feadc5b324cde completed May 22, 2026, 12:27 p.m.
Created at: April 18, 2026, 6:06 a.m.