Triple

T22730911
Position Surface form Disambiguated ID Type / Status
Subject 2018 Russian presidential election E562130 entity
Predicate mainOpponent P437 FINISHED
Object Pavel Grudinin
Pavel Grudinin is a Russian agribusiness executive and politician who gained national prominence as the Communist Party’s candidate in the 2018 Russian presidential election.
E2289739 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 Grudinin | Statement: [2018 Russian presidential election, mainOpponent, Pavel Grudinin]
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 Grudinin
Triple: [2018 Russian presidential election, mainOpponent, Pavel Grudinin]
Generated description
Pavel Grudinin is a Russian agribusiness executive and politician who gained national prominence as the Communist Party’s candidate in the 2018 Russian presidential election.

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_69e24550859c81908727d91efc3a81b4 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1792cb9cc8190a7c45032427bca1a completed April 29, 2026, 3:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5b66d3195c81908f45f41440eced22 completed July 18, 2026, 11:43 a.m.
NEDg Description generation batch_6a5b675ecbc081909753aff758ef3576 completed July 18, 2026, 11:45 a.m.
NED2 Entity disambiguation (via description) batch_6a5b68075c2c819089e91500f6b23df0 completed July 18, 2026, 11:48 a.m.
Created at: April 17, 2026, 3:21 p.m.