Triple

T2477846
Position Surface form Disambiguated ID Type / Status
Subject Selected Reserve E55130 entity
Predicate hasAbbreviation P43 FINISHED
Object SELRES E269891 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: SELRES | Statement: [Selected Reserve, hasAbbreviation, SELRES]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SELRES
Context triple: [Selected Reserve, hasAbbreviation, SELRES]
  • A. SELRES chosen
    SELRES is the commonly used abbreviation for the Selected Reserve, the primary pool of trained military reservists who are ready for rapid mobilization and deployment.
  • B. SRES
    SRES is the School of Resources and Environmental Science at Wuhan University, a faculty focused on education and research in natural resources, geography, and environmental science.
  • C. RSE
    RSE is the commonly used abbreviation for the Royal Society of Edinburgh, Scotland’s national academy of science and letters.
  • D. SEBL
    SEBL was the stock ticker symbol for Siebel Systems, a prominent customer relationship management (CRM) software company later acquired by Oracle.
  • E. Resuk
    Resuk is an indigenous local language spoken by the community on Atauro Island in Timor-Leste.
  • 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_69ab49e279e88190ab10d7248aea9d11 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd14ef7d081909159be158bc0ce45 completed March 7, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69af1f8990488190bc54cc5eadf11baa completed March 9, 2026, 7:29 p.m.
Created at: March 6, 2026, 9:45 p.m.