Triple

T23698042
Position Surface form Disambiguated ID Type / Status
Subject Abtai Sain Khan E585505 entity
Predicate positionHeld P8 FINISHED
Object Tushetu Khan
Tushetu Khan was a prominent Mongol princely title and khanate in Outer Mongolia, historically associated with the lineage of Abtai Sain Khan and influential in the region’s political and religious affairs.
E1686373 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: Tushetu Khan | Statement: [Abtai Sain Khan, positionHeld, Tushetu Khan]
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: Tushetu Khan
Triple: [Abtai Sain Khan, positionHeld, Tushetu Khan]
Generated description
Tushetu Khan was a prominent Mongol princely title and khanate in Outer Mongolia, historically associated with the lineage of Abtai Sain Khan and influential in the region’s political and religious affairs.

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_69e24904bd508190abfcb74855de2918 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b6804970819083d4e63caa93ae4e completed April 29, 2026, 7:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10b6f7125c8190baefa15d58e6211a completed May 22, 2026, 8:05 p.m.
NEDg Description generation batch_6a10b82504908190904c1ed84610e0c4 completed May 22, 2026, 8:10 p.m.
NED2 Entity disambiguation (via description) batch_6a10b97dedd48190858687f050f15f7b completed May 22, 2026, 8:15 p.m.
Created at: April 17, 2026, 6:53 p.m.