Triple

T25503152
Position Surface form Disambiguated ID Type / Status
Subject Fedorov E639173 entity
Predicate hasNotableBearer P458 FINISHED
Object Pavel Fedorov
Pavel Fedorov is a personal name shared by multiple individuals, most commonly of Russian origin, whose specific notable identity is not uniquely determined from the given information.
E1696463 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: Pavel Fedorov | Statement: [Fedorov, hasNotableBearer, Pavel Fedorov]
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: Pavel Fedorov
Triple: [Fedorov, hasNotableBearer, Pavel Fedorov]
Generated description
Pavel Fedorov is a personal name shared by multiple individuals, most commonly of Russian origin, whose specific notable identity is not uniquely determined from the given information.

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_69e75dbd09308190b6b5f0afdc12ec6d completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f80381a481909f39b55b220ad261 completed May 2, 2026, 1:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10d9ec5d40819081c02079a814c4e7 completed May 22, 2026, 10:34 p.m.
NEDg Description generation batch_6a10dc54e00c8190b6e45779b281bc2a completed May 22, 2026, 10:44 p.m.
NED2 Entity disambiguation (via description) batch_6a10dcaf4bd48190b5ed702e33b40441 completed May 22, 2026, 10:46 p.m.
Created at: April 21, 2026, 2:45 p.m.