Triple

T35497461
Position Surface form Disambiguated ID Type / Status
Subject King Chungmok of Goryeo E1025907 entity
Predicate father P120 FINISHED
Object King Chunghye of Goryeo
King Chunghye of Goryeo was a 14th-century monarch of Korea’s Goryeo dynasty known for his turbulent reign marked by political instability and personal scandal.
E2181708 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: King Chunghye of Goryeo | Statement: [King Chungmok of Goryeo, father, King Chunghye of Goryeo]
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: King Chunghye of Goryeo
Triple: [King Chungmok of Goryeo, father, King Chunghye of Goryeo]
Generated description
King Chunghye of Goryeo was a 14th-century monarch of Korea’s Goryeo dynasty known for his turbulent reign marked by political instability and personal scandal.

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_69f76dfc9c60819089c4217d93922615 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79734314081908959513c93b599e8 completed May 3, 2026, 6:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39b412c9a88190b38262829b47d2b9 completed June 22, 2026, 10:15 p.m.
NEDg Description generation batch_6a39b6ab693881909c9f3c227f06817c completed June 22, 2026, 10:26 p.m.
NED2 Entity disambiguation (via description) batch_6a39b7d4ad24819097dde86914af826c completed June 22, 2026, 10:31 p.m.
Created at: May 3, 2026, 4:04 p.m.