Triple

T12921337
Position Surface form Disambiguated ID Type / Status
Subject ECO Science Foundation E309128 entity
Predicate abbreviation P43 FINISHED
Object ECOSF E78723 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: ECOSF | Statement: [ECO Science Foundation, abbreviation, ECOSF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ECOSF
Context triple: [ECO Science Foundation, abbreviation, ECOSF]
  • A. ECOSOCC
    ECOSOCC is an advisory organ of the African Union that represents civil society organizations and promotes dialogue on economic, social, and cultural issues across the continent.
  • B. ECASA
    ECASA is a Cuban state-owned company responsible for managing and operating the country’s civil airports and air terminals.
  • C. ECO chosen
    ECO (Economic Cooperation Organization) is a regional intergovernmental organization that promotes economic, technical, and cultural cooperation among countries in Eurasia, particularly in Central and South Asia and the Middle East.
  • D. ECI
    ECI is the independent constitutional authority responsible for administering and supervising elections in India at the national and state levels.
  • E. ECOTY
    ECOTY is the commonly used acronym for the European Car of the Year, a prestigious annual automotive award judged by motoring journalists from across Europe.
  • 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_69d7bdf92b588190acdf2a2291ac4590 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d971e7f6e881908c7bb12283898c80 completed April 10, 2026, 9:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6af5ffcc48190bf93ce32e4aecfcd completed May 3, 2026, 2:13 a.m.
Created at: April 9, 2026, 5:41 p.m.