Triple

T24280540
Position Surface form Disambiguated ID Type / Status
Subject Hyundai Mipo Dockyard E605526 entity
Predicate hasShipyard P4334 FINISHED
Object Ulsan shipyard
Ulsan shipyard is a major South Korean shipbuilding facility in Ulsan, renowned as one of the world’s largest and most advanced shipyards.
E1634142 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: Ulsan shipyard | Statement: [Hyundai Mipo Dockyard, hasShipyard, Ulsan shipyard]
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: Ulsan shipyard
Triple: [Hyundai Mipo Dockyard, hasShipyard, Ulsan shipyard]
Generated description
Ulsan shipyard is a major South Korean shipbuilding facility in Ulsan, renowned as one of the world’s largest and most advanced shipyards.

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_69e295480d0c8190846fc3c2e2da1d4c completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f28f5227888190b1713af150fa30a1 completed April 29, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fe34945f08190bc0c7146564ff58f completed May 22, 2026, 5:02 a.m.
NEDg Description generation batch_6a0fe464435c8190aed7a4a6496ab3f5 completed May 22, 2026, 5:06 a.m.
NED2 Entity disambiguation (via description) batch_6a0fe55f1c888190864ef29ab6945f5a completed May 22, 2026, 5:10 a.m.
Created at: April 18, 2026, 12:07 a.m.