Triple

T3767743
Position Surface form Disambiguated ID Type / Status
Subject European Audiovisual Observatory E82719 entity
Predicate abbreviation P43 FINISHED
Object EAO E82719 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: EAO | Statement: [European Audiovisual Observatory, abbreviation, EAO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EAO
Context triple: [European Audiovisual Observatory, abbreviation, EAO]
  • A. EAO chosen
    EAO is the acronym for the European Audiovisual Observatory, an organization that collects and disseminates data and analysis on the audiovisual industry in Europe.
  • B. RAEOA
    RAEOA is the autonomous administrative region of Oecusse in Timor-Leste, formally known as the Special Administrative Region of Oecusse-Ambeno.
  • C. AO
    AO is the commonly used abbreviation for the Administrative Office of the United States Courts, the federal agency that provides administrative support to the U.S. federal judiciary.
  • D. AO
    AO is the vehicle registration code used on license plates for vehicles registered in Italy’s Aosta Valley region.
  • E. AO
    AO is the two-letter ISO 3166-1 alpha-2 country code representing Angola in international standards and systems.
  • 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_69ad8b207b0081909d2b48843fbd8795 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcc2bdf6c819088d3c6ace83ca5ea completed March 8, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4e5251d2481909f692937271a8013 completed March 14, 2026, 4:33 a.m.
Created at: March 8, 2026, 3:35 p.m.