Triple

T27086844
Position Surface form Disambiguated ID Type / Status
Subject shoot wrestling E686057 entity
Predicate hasKeyFigure P810 FINISHED
Object Akira Maeda
Akira Maeda is a pioneering Japanese professional wrestler and mixed martial arts innovator, best known for popularizing shoot-style wrestling and founding the influential promotion RINGS.
E2297928 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: Akira Maeda | Statement: [shoot wrestling, hasKeyFigure, Akira Maeda]
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: Akira Maeda
Triple: [shoot wrestling, hasKeyFigure, Akira Maeda]
Generated description
Akira Maeda is a pioneering Japanese professional wrestler and mixed martial arts innovator, best known for popularizing shoot-style wrestling and founding the influential promotion RINGS.

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_69ef148940ec819097b5c20fbfbf7c81 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f62346348081909de57928856e2c8b completed May 2, 2026, 4:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a83fb1cb26c8190a04abcc8243ec897 completed Aug. 18, 2026, 6:26 a.m.
NEDg Description generation batch_6a840170224c81909ff871d146e80321 completed Aug. 18, 2026, 6:53 a.m.
NED2 Entity disambiguation (via description) batch_6a8402056dd88190b3f381ea199f2b57 completed Aug. 18, 2026, 6:56 a.m.
Created at: April 27, 2026, 8:38 a.m.