Triple

T25018762
Position Surface form Disambiguated ID Type / Status
Subject Seoul Ring Expressway E626214 entity
Predicate routeNumber P1864 FINISHED
Object Expressway 100
Expressway 100 is a major South Korean orbital highway encircling the Seoul metropolitan area, commonly known as the Seoul Ring Expressway.
 E1662808 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: Expressway 100 | Statement: [Seoul Ring Expressway, routeNumber, Expressway 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: Expressway 100
Triple: [Seoul Ring Expressway, routeNumber, Expressway 100]
Generated description
Expressway 100 is a major South Korean orbital highway encircling the Seoul metropolitan area, commonly known as the Seoul Ring Expressway.

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_6a104bbb9b6c81908fcc21c8c027b9de completed May 22, 2026, 12:27 p.m.
Created at: April 18, 2026, 6:06 a.m.