Triple

T36199277
Position Surface form Disambiguated ID Type / Status
Subject UFC lightweight division E1047213 entity
Predicate notableContender P26163 FINISHED
Object Arman Tsarukyan
Arman Tsarukyan is an elite Armenian-Russian mixed martial artist known for his high-paced wrestling-heavy style and rising status as a top contender in the UFC lightweight division.
E2175698 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: Arman Tsarukyan | Statement: [UFC lightweight division, notableContender, Arman Tsarukyan]
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: Arman Tsarukyan
Triple: [UFC lightweight division, notableContender, Arman Tsarukyan]
Generated description
Arman Tsarukyan is an elite Armenian-Russian mixed martial artist known for his high-paced wrestling-heavy style and rising status as a top contender in the UFC lightweight division.

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_69f76e414bdc8190996f15a544220a3d completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b534d7b081909a0a382d3a52a230 completed May 3, 2026, 8:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a394d2c266c81908c6e721e7902fe5a completed June 22, 2026, 2:56 p.m.
NEDg Description generation batch_6a394fef41948190838c6eb519889640 completed June 22, 2026, 3:08 p.m.
NED2 Entity disambiguation (via description) batch_6a39650190008190b98773a0671af2a0 completed June 22, 2026, 4:38 p.m.
Created at: May 3, 2026, 4:08 p.m.