Triple

T28589828
Position Surface form Disambiguated ID Type / Status
Subject Late Tang warlord era E723610 entity
Predicate notableFigure P4290 FINISHED
Object Li Keyong
Li Keyong was a prominent Shatuo Turkic military governor and warlord of the late Tang dynasty who played a key role in the power struggles that led to the Five Dynasties period.
E1834668 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: Li Keyong | Statement: [Late Tang warlord era, notableFigure, Li Keyong]
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: Li Keyong
Triple: [Late Tang warlord era, notableFigure, Li Keyong]
Generated description
Li Keyong was a prominent Shatuo Turkic military governor and warlord of the late Tang dynasty who played a key role in the power struggles that led to the Five Dynasties 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_69f01d7f92e481909847f5f3f3174a89 completed April 28, 2026, 2:37 a.m.
NER Named-entity recognition batch_69f651b2a2388190b269d7b5e931794a completed May 2, 2026, 7:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24a238190c8190bad49859ef5627f5 completed June 6, 2026, 10:42 p.m.
NEDg Description generation batch_6a24a638e30881908d94bc85bfb4b3a4 completed June 6, 2026, 10:59 p.m.
NED2 Entity disambiguation (via description) batch_6a24b191b75c8190842a72cd498304fe completed June 6, 2026, 11:47 p.m.
Created at: April 28, 2026, 4:19 a.m.