Triple

T38292018
Position Surface form Disambiguated ID Type / Status
Subject Queen Noguk E1022384 entity
Predicate burialPlace P196 FINISHED
Object Guri, Gyeonggi Province, Korea
Guri, in Gyeonggi Province, South Korea, is a city just east of Seoul known for its historical sites, including royal tombs from the Goryeo and Joseon periods.
E2264593 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: Guri, Gyeonggi Province, Korea | Statement: [Queen Noguk, burialPlace, Guri, Gyeonggi Province, Korea]
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: Guri, Gyeonggi Province, Korea
Triple: [Queen Noguk, burialPlace, Guri, Gyeonggi Province, Korea]
Generated description
Guri, in Gyeonggi Province, South Korea, is a city just east of Seoul known for its historical sites, including royal tombs from the Goryeo and Joseon periods.

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_69f76df190f081908d5aa02c8a9286d0 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fcc5dfe18c81908e2c56964feaedd6 completed May 7, 2026, 5:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a419dff6d108190948ef08e5a83d81f completed June 28, 2026, 10:19 p.m.
NEDg Description generation batch_6a419f84ea508190b7c047c6b307f20a completed June 28, 2026, 10:26 p.m.
NED2 Entity disambiguation (via description) batch_6a41a004529c819086ae5310f9b30c47 completed June 28, 2026, 10:28 p.m.
Created at: May 3, 2026, 4:30 p.m.