Triple

T26880663
Position Surface form Disambiguated ID Type / Status
Subject Anatoly Stessel E676883 entity
Predicate familyName P18 FINISHED
Object Stessel
Stessel is a surname most notably associated with Anatoly Stessel, a Russian Imperial Army general involved in the Russo-Japanese War.
E1743509 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: Stessel | Statement: [Anatoly Stessel, familyName, Stessel]
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: Stessel
Triple: [Anatoly Stessel, familyName, Stessel]
Generated description
Stessel is a surname most notably associated with Anatoly Stessel, a Russian Imperial Army general involved in the Russo-Japanese War.

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_69eee9bb44988190b6e11652d028bc59 completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61f1c9c888190a3b8711c2d35036b completed May 2, 2026, 3:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1213675e7481908552e7b643b39b1e completed May 23, 2026, 8:51 p.m.
NEDg Description generation batch_6a121575b8b88190bb24b666bbf94da7 completed May 23, 2026, 9 p.m.
NED2 Entity disambiguation (via description) batch_6a1215e830648190afc5de590a2a2cc1 completed May 23, 2026, 9:02 p.m.
Created at: April 27, 2026, 5:39 a.m.