Triple

T26241317
Position Surface form Disambiguated ID Type / Status
Subject Lyubov Kosmodemyanskaya E656321 entity
Predicate relative P37 FINISHED
Object Pyotr Kosmodemyansky
Pyotr Kosmodemyansky was a Soviet military officer and Hero of the Soviet Union, known as the brother of famed partisan Zoya Kosmodemyanskaya.
E1732902 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: Pyotr Kosmodemyansky | Statement: [Lyubov Kosmodemyanskaya, relative, Pyotr Kosmodemyansky]
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: Pyotr Kosmodemyansky
Triple: [Lyubov Kosmodemyanskaya, relative, Pyotr Kosmodemyansky]
Generated description
Pyotr Kosmodemyansky was a Soviet military officer and Hero of the Soviet Union, known as the brother of famed partisan Zoya Kosmodemyanskaya.

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_69ee5b4c59a881909d9ee4fd013fffd5 completed April 26, 2026, 6:37 p.m.
NER Named-entity recognition batch_69f60d8f7f9c8190bb8cb8f8ac4c0ca5 completed May 2, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11c7f1677081909c27f7bd222582ca completed May 23, 2026, 3:29 p.m.
NEDg Description generation batch_6a11c945273c8190ac0bc6fe508a6d9a completed May 23, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_6a11ca68b0488190851b0634a0c784bd completed May 23, 2026, 3:40 p.m.
Created at: April 26, 2026, 9:03 p.m.