Triple

T35526443
Position Surface form Disambiguated ID Type / Status
Subject Fedor Emelianenko E1026682 entity
Predicate relative P37 FINISHED
Object Aleksander Emelianenko
Aleksander Emelianenko is a Russian mixed martial artist and heavyweight fighter known for competing in major promotions such as PRIDE and M-1 Global.
E2150692 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: Aleksander Emelianenko | Statement: [Fedor Emelianenko, relative, Aleksander Emelianenko]
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: Aleksander Emelianenko
Triple: [Fedor Emelianenko, relative, Aleksander Emelianenko]
Generated description
Aleksander Emelianenko is a Russian mixed martial artist and heavyweight fighter known for competing in major promotions such as PRIDE and M-1 Global.

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_69f76dfe78b081908e2b14cb88dd8c00 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f797ce98548190936030999f601939 completed May 3, 2026, 6:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38726e7b208190ba13cd76ae43017d completed June 21, 2026, 11:23 p.m.
NEDg Description generation batch_6a38731e9da88190b4e9158b234e20da completed June 21, 2026, 11:26 p.m.
NED2 Entity disambiguation (via description) batch_6a387377a850819080349b2f0c461bc6 completed June 21, 2026, 11:27 p.m.
Created at: May 3, 2026, 4:04 p.m.