Triple

T35673135
Position Surface form Disambiguated ID Type / Status
Subject UFC Heavyweight Championship E1030778 entity
Predicate formerChampion P28766 FINISHED
Object Maurice Smith
Maurice Smith is an American kickboxer and mixed martial artist renowned as a pioneering striker in MMA who captured the UFC heavyweight title in the late 1990s.
E2151824 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: Maurice Smith | Statement: [UFC Heavyweight Championship, formerChampion, Maurice Smith]
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: Maurice Smith
Triple: [UFC Heavyweight Championship, formerChampion, Maurice Smith]
Generated description
Maurice Smith is an American kickboxer and mixed martial artist renowned as a pioneering striker in MMA who captured the UFC heavyweight title in the late 1990s.

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_69f76e0acfc0819082c8495c2210ce73 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_6a006c7770e88190b18e56444404b2e4 completed May 10, 2026, 11:31 a.m.
NED1 Entity disambiguation (via context triple) batch_6a38728518848190a9cf4dbafe1910cf completed June 21, 2026, 11:23 p.m.
NEDg Description generation batch_6a387348579c81909fd91162bbf8792c completed June 21, 2026, 11:27 p.m.
NED2 Entity disambiguation (via description) batch_6a38744cbac081908be126066e8e79e5 completed June 21, 2026, 11:31 p.m.
Created at: May 3, 2026, 4:05 p.m.