Triple

T35629994
Position Surface form Disambiguated ID Type / Status
Subject Russia national athletics team E1029555 entity
Predicate hasNotableAthletes P10392 FINISHED
Object Anna Chicherova
Anna Chicherova is a Russian high jumper and Olympic champion known for winning gold at the 2012 London Games and multiple World Championship medals.
E2288565 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: Anna Chicherova | Statement: [Russia national athletics team, hasNotableAthletes, Anna Chicherova]
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: Anna Chicherova
Triple: [Russia national athletics team, hasNotableAthletes, Anna Chicherova]
Generated description
Anna Chicherova is a Russian high jumper and Olympic champion known for winning gold at the 2012 London Games and multiple World Championship medals.

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_69f76e07bb0c8190968ea2d836fc42c9 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_6a03809b0390819096079bac5444f38b completed May 12, 2026, 7:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5a9c8bcf588190a98ad904d114757c completed July 17, 2026, 9:20 p.m.
NEDg Description generation batch_6a5a9de21de08190b634c577e7d91f55 completed July 17, 2026, 9:25 p.m.
NED2 Entity disambiguation (via description) batch_6a5a9e330b48819095a9b8a8b6b9351d completed July 17, 2026, 9:27 p.m.
Created at: May 3, 2026, 4:05 p.m.