Triple

T18635755
Position Surface form Disambiguated ID Type / Status
Subject APSIA E455542 entity
Predicate abbreviation P43 FINISHED
Object APSIA NE NERFINISHED

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: APSIA | Statement: [APSIA, abbreviation, APSIA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: APSIA
Context triple: [APSIA, abbreviation, APSIA]
  • A. APSIA chosen
    APSIA is a global association of leading graduate schools that specialize in international affairs, public policy, and related fields.
  • B. ACSIS
    ACSIS is a digital autocorrelation spectrometer system used on the James Clerk Maxwell Telescope to analyze submillimetre astronomical signals with high spectral resolution.
  • C. IAIS
    IAIS is a global standard-setting body that brings together insurance regulators and supervisors to promote effective and consistent supervision of the insurance industry worldwide.
  • D. IAIS
    IAIS is the reporting mark for the Iowa Interstate Railroad, a regional freight railroad operating primarily in Iowa and Illinois.
  • E. Information Processing Society of Japan
    The Information Processing Society of Japan is a leading Japanese professional organization dedicated to advancing research, education, and industry collaboration in computer science and information technology.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38cc7948190a55ea64e5638994e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e54fc90b508190849cecb462b52b62 completed April 19, 2026, 9:57 p.m.
Created at: April 10, 2026, 11:46 a.m.