Triple

T35411582
Position Surface form Disambiguated ID Type / Status
Subject King of Goryeo E1023525 entity
Predicate titleHolder P1911 FINISHED
Object Sinjong of Goryeo
Sinjong of Goryeo was a monarch of Korea’s Goryeo dynasty who reigned in the late 12th century during a period of political turbulence and military dominance over the royal court.
E2160980 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: Sinjong of Goryeo | Statement: [King of Goryeo, titleHolder, Sinjong 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: Sinjong of Goryeo
Triple: [King of Goryeo, titleHolder, Sinjong of Goryeo]
Generated description
Sinjong of Goryeo was a monarch of Korea’s Goryeo dynasty who reigned in the late 12th century during a period of political turbulence and military dominance over the royal court.

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_69f76df54bac8190bd0d3b0eb35cda5f completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f795672b40819087ccce744e044124 completed May 3, 2026, 6:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38ae0cb6cc8190b70b5c1681bd6c73 completed June 22, 2026, 3:37 a.m.
NEDg Description generation batch_6a38af3780a48190b23089b4d66b3311 completed June 22, 2026, 3:42 a.m.
NED2 Entity disambiguation (via description) batch_6a38afae6574819096f015f9d1c3eaca completed June 22, 2026, 3:44 a.m.
Created at: May 3, 2026, 4:03 p.m.