Triple

T22915906
Position Surface form Disambiguated ID Type / Status
Subject Gracie Humaitá E568731 entity
Predicate producedAthlete P17934 FINISHED
Object Megumi Fujii
Megumi Fujii is a pioneering Japanese mixed martial artist and submission grappling specialist widely regarded as one of the greatest female fighters in MMA history.
E1680124 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: Megumi Fujii | Statement: [Gracie Humaitá, producedAthlete, Megumi Fujii]
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: Megumi Fujii
Triple: [Gracie Humaitá, producedAthlete, Megumi Fujii]
Generated description
Megumi Fujii is a pioneering Japanese mixed martial artist and submission grappling specialist widely regarded as one of the greatest female fighters in MMA history.

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_69e2458d90c88190a58cead4e781ca6a completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18079217481908db98882929ac69a completed April 29, 2026, 3:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a108946065c8190a084764180ca30fc completed May 22, 2026, 4:50 p.m.
NEDg Description generation batch_6a108b13f26c81908a4d0ea4bdfa605c completed May 22, 2026, 4:57 p.m.
NED2 Entity disambiguation (via description) batch_6a108b8ea6908190b8f6887610e5d6a3 completed May 22, 2026, 4:59 p.m.
Created at: April 17, 2026, 3:42 p.m.