Triple

T6519557
Position Surface form Disambiguated ID Type / Status
Subject SRU E148346 entity
Predicate hasAcronym P43 FINISHED
Object SRU E148346 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: SRU | Statement: [SRU, hasAcronym, SRU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SRU
Context triple: [SRU, hasAcronym, SRU]
  • A. SRU chosen
    SRU (Search/Retrieve via URL) is a standard web-based search protocol that enables querying and retrieving information from remote databases using URLs and XML.
  • B. SRL
    SRL is a peer-reviewed scientific journal that publishes research and reports on seismology and earthquake science.
  • C. SRG
    SRG is the IATA airport code for Jenderal Ahmad Yani International Airport serving Semarang, Indonesia.
  • D. SRF
    SRF is a French filmmakers' association best known for organizing the Directors' Fortnight sidebar at the Cannes Film Festival and advocating for directors' artistic and professional interests.
  • E. SRF
    SRF is the German-language division of the Swiss Broadcasting Corporation, responsible for producing and broadcasting radio, television, and online content in German-speaking Switzerland.
  • 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_69c687e68e748190baceb9298f32d3ed completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6ac11d0e481908103c4b51de9521e completed March 27, 2026, 4:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d51af5308190928c97ceb5d5fa2d completed March 27, 2026, 7:06 p.m.
Created at: March 27, 2026, 1:45 p.m.