Triple

T27848810
Position Surface form Disambiguated ID Type / Status
Subject Guiyi Circuit E703894 entity
Predicate notableRuler P22 FINISHED
Object Cao Yijin
Cao Yijin was a prominent 10th-century warlord and de facto ruler in northwestern China who consolidated power in the Hexi region during the Five Dynasties and Ten Kingdoms period.
E1858087 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: Cao Yijin | Statement: [Guiyi Circuit, notableRuler, Cao Yijin]
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: Cao Yijin
Triple: [Guiyi Circuit, notableRuler, Cao Yijin]
Generated description
Cao Yijin was a prominent 10th-century warlord and de facto ruler in northwestern China who consolidated power in the Hexi region during the Five Dynasties and Ten Kingdoms period.

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_69ef840d9e3c819093615ebff4ec22be completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f63902f71c8190b26ac186ad00acbf completed May 2, 2026, 5:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2588f4de7c81909bb236f0b9271e30 completed June 7, 2026, 3:06 p.m.
NEDg Description generation batch_6a258d02bfa48190aaf6c5683a020fdf completed June 7, 2026, 3:23 p.m.
NED2 Entity disambiguation (via description) batch_6a258ef2f8ac8190912799796e2968cc completed June 7, 2026, 3:32 p.m.
Created at: April 27, 2026, 6:09 p.m.