Triple

T22968171
Position Surface form Disambiguated ID Type / Status
Subject Demian Maia E571105 entity
Predicate fullName P16 FINISHED
Object Demian Augusto Maia Baptista
Demian Augusto Maia Baptista is a Brazilian mixed martial artist and Brazilian jiu-jitsu specialist renowned for his elite grappling skills and successful career in the UFC.
E1607330 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: Demian Augusto Maia Baptista | Statement: [Demian Maia, fullName, Demian Augusto Maia Baptista]
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: Demian Augusto Maia Baptista
Triple: [Demian Maia, fullName, Demian Augusto Maia Baptista]
Generated description
Demian Augusto Maia Baptista is a Brazilian mixed martial artist and Brazilian jiu-jitsu specialist renowned for his elite grappling skills and successful career in the UFC.

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_69e245b2c6548190a0e4c7f2f7df2d48 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f182301f388190bb39e3d5b356dc65 completed April 29, 2026, 3:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f75e19e7081909195f1ff22f686ac completed May 21, 2026, 9:15 p.m.
NEDg Description generation batch_6a0f76cc78748190b0f22716094bba19 completed May 21, 2026, 9:19 p.m.
NED2 Entity disambiguation (via description) batch_6a0f77541b948190bb866a8c7c6f5ca9 completed May 21, 2026, 9:21 p.m.
Created at: April 17, 2026, 3:48 p.m.