Triple

T29842398
Position Surface form Disambiguated ID Type / Status
Subject Pavlova E757835 entity
Predicate hasNotableBearer P458 FINISHED
Object Galina Pavlova
Galina Pavlova is a Russian ballet dancer and choreographer known for her performances with major ballet companies and contributions to classical dance.
E2111487 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: Galina Pavlova | Statement: [Pavlova, hasNotableBearer, Galina Pavlova]
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: Galina Pavlova
Triple: [Pavlova, hasNotableBearer, Galina Pavlova]
Generated description
Galina Pavlova is a Russian ballet dancer and choreographer known for her performances with major ballet companies and contributions to classical dance.

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_69f224593f6c81908785a560fe659f58 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f6760b3d6081909d0e3748483989a4 completed May 2, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37660ababc8190b81679d34aa60088 completed June 21, 2026, 4:18 a.m.
NEDg Description generation batch_6a3768b4557c8190b6c4b370726e5b50 completed June 21, 2026, 4:29 a.m.
NED2 Entity disambiguation (via description) batch_6a376918bbb8819081ac8dee61a027f2 completed June 21, 2026, 4:31 a.m.
Created at: April 29, 2026, 5:40 p.m.