Triple

T35492888
Position Surface form Disambiguated ID Type / Status
Subject Yuji Nagata E1025776 entity
Predicate hasFeudWith P16446 FINISHED
Object Tadao Yasuda
Tadao Yasuda is a former Japanese professional wrestler and mixed martial artist, best known for his time in New Japan Pro-Wrestling and his earlier career as a sumo wrestler.
E2145060 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: Tadao Yasuda | Statement: [Yuji Nagata, hasFeudWith, Tadao Yasuda]
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: Tadao Yasuda
Triple: [Yuji Nagata, hasFeudWith, Tadao Yasuda]
Generated description
Tadao Yasuda is a former Japanese professional wrestler and mixed martial artist, best known for his time in New Japan Pro-Wrestling and his earlier career as a sumo wrestler.

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_69f76dfbcdd881908c7b0b6bc502252b completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7972f535081908b76e690607ebb6b completed May 3, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a384a2ce6dc8190862796cbbfb59f33 completed June 21, 2026, 8:31 p.m.
NEDg Description generation batch_6a384aa84b748190824a5fa4f797bdca completed June 21, 2026, 8:33 p.m.
NED2 Entity disambiguation (via description) batch_6a384e5cdc388190b78a84212c06a3ee completed June 21, 2026, 8:49 p.m.
Created at: May 3, 2026, 4:04 p.m.