Triple

T27086262
Position Surface form Disambiguated ID Type / Status
Subject Federal Service for Technical and Export Control E686041 entity
Predicate hasAbbreviation P43 FINISHED
Object FSTEC of Russia
FSTEC of Russia is a Russian government agency responsible for overseeing information security, technical protection of confidential data, and export control of sensitive technologies.
E1753343 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: FSTEC of Russia | Statement: [Federal Service for Technical and Export Control, hasAbbreviation, FSTEC of Russia]
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: FSTEC of Russia
Triple: [Federal Service for Technical and Export Control, hasAbbreviation, FSTEC of Russia]
Generated description
FSTEC of Russia is a Russian government agency responsible for overseeing information security, technical protection of confidential data, and export control of sensitive technologies.

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_69ef148940ec819097b5c20fbfbf7c81 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f62346348081909de57928856e2c8b completed May 2, 2026, 4:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a123ae3caf881909fb1447b52532be4 completed May 23, 2026, 11:40 p.m.
NEDg Description generation batch_6a123b72e22481909d5880a4b686b3e0 completed May 23, 2026, 11:42 p.m.
NED2 Entity disambiguation (via description) batch_6a123c1061ac8190b8becdcf391832f8 completed May 23, 2026, 11:45 p.m.
Created at: April 27, 2026, 8:38 a.m.