Triple

T34036745
Position Surface form Disambiguated ID Type / Status
Subject Oryukdo Islets E872819 entity
Predicate hasPart P35 FINISHED
Object Usakdo
Usakdo is one of the small rocky islets that make up South Korea’s Oryukdo Islets, known for their coastal scenery and marine wildlife.
E2079527 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: Usakdo | Statement: [Oryukdo Islets, hasPart, Usakdo]
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: Usakdo
Triple: [Oryukdo Islets, hasPart, Usakdo]
Generated description
Usakdo is one of the small rocky islets that make up South Korea’s Oryukdo Islets, known for their coastal scenery and marine wildlife.

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_69f349a3363081909cea4c9a848cefe2 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f70b3ca6788190a6293647a71e3071 completed May 3, 2026, 8:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36a03634408190973233703a87ee9a completed June 20, 2026, 2:14 p.m.
NEDg Description generation batch_6a36a0c43d388190aa3499b2353aa31b completed June 20, 2026, 2:16 p.m.
NED2 Entity disambiguation (via description) batch_6a36a16a05a48190aac973a431bb7cc7 completed June 20, 2026, 2:19 p.m.
Created at: May 1, 2026, 1:51 a.m.