Triple

T10127786
Position Surface form Disambiguated ID Type / Status
Subject GEKE E226258 entity
Predicate abbreviation P43 FINISHED
Object GEKE E226258 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: GEKE | Statement: [GEKE, abbreviation, GEKE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GEKE
Context triple: [GEKE, abbreviation, GEKE]
  • A. GEKE chosen
    GEKE is the German abbreviation for the Community of Protestant Churches in Europe, a fellowship of Protestant churches committed to mutual recognition and cooperation across the continent.
  • B. GEKUT
    GEKUT is the UN/LOCODE identifier for the city of Kutaisi in Georgia, used in international trade and transport logistics.
  • C. GE
    GE is the abbreviation for ICANN’s Government Engagement function, which manages and coordinates ICANN’s relationships and interactions with governments and intergovernmental organizations worldwide.
  • D. GE
    GE is the Swiss canton code for Geneva, a major city and canton in western Switzerland known for its international organizations and financial center.
  • E. GE
    GE is the ISO 3166-1 alpha-2 country code for Georgia, a nation at the crossroads of Eastern Europe and Western Asia.
  • 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_69ca843057b48190a86730167f5d6b98 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cdd2f0a0e881909267a83fbeb31f0c completed April 2, 2026, 2:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cc72848481909dcbfc9fe3f6d379 completed April 5, 2026, 8:56 p.m.
Created at: March 30, 2026, 9:05 p.m.