Triple

T38532786
Position Surface form Disambiguated ID Type / Status
Subject Russian Federation military ranks E923410 entity
Predicate hasNavalEnlistedRank P198889 FINISHED
Object Senior Seaman
Senior Seaman is a non-commissioned naval rank in the Russian Federation, typically held by experienced enlisted sailors below petty officers.
E2275246 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: Senior Seaman | Statement: [Russian Federation military ranks, hasNavalEnlistedRank, Senior Seaman]
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: Senior Seaman
Triple: [Russian Federation military ranks, hasNavalEnlistedRank, Senior Seaman]
Generated description
Senior Seaman is a non-commissioned naval rank in the Russian Federation, typically held by experienced enlisted sailors below petty officers.

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_69f76ea8f6348190a5c03fb6292bbee3 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69ffec376dd4819089fd9551deaa2fe3 completed May 10, 2026, 2:23 a.m.
NED1 Entity disambiguation (via context triple) batch_6a41e02ad6dc8190a35c096914a2097e completed June 29, 2026, 3:02 a.m.
NEDg Description generation batch_6a41e3f50b8481909892dc991df7eebc completed June 29, 2026, 3:18 a.m.
NED2 Entity disambiguation (via description) batch_6a41e44731988190abc73f2fc2e9155b completed June 29, 2026, 3:19 a.m.
Created at: May 3, 2026, 4:32 p.m.