Triple

T5799349
Position Surface form Disambiguated ID Type / Status
Subject Security Sector Reform Unit E128582 entity
Predicate abbreviation P43 FINISHED
Object SSR Unit E128599 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: SSR Unit | Statement: [Security Sector Reform Unit, abbreviation, SSR Unit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SSR Unit
Context triple: [Security Sector Reform Unit, abbreviation, SSR Unit]
  • A. SSR
    SSR is the Swiss Broadcasting Corporation, Switzerland’s national public service broadcaster providing radio, television, and online media in multiple languages.
  • B. SSR Advisory Team chosen
    The SSR Advisory Team is a specialized unit that provides expert guidance and support on security sector reform within United Nations peace operations.
  • C. SSU
    SSU is a public liberal arts university located in Rohnert Park, California, known for its strong programs in the arts, sciences, and education.
  • D. SRG SSR
    SRG SSR is Switzerland’s national public broadcasting organization, providing multilingual radio, television, and online services across the country.
  • E. SSV
    SSV is a lightweight, off-road side-by-side vehicle class commonly used in rally raid competitions for its agility and versatility over rough terrain.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c00846a0d881909e46841f8e156b64 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02acb12c081908e4beee4a957f9f9 completed March 22, 2026, 5:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69c09833017c81908da09127e8455cb6 completed March 23, 2026, 1:32 a.m.
Created at: March 22, 2026, 3:52 p.m.