Triple

T1316744
Position Surface form Disambiguated ID Type / Status
Subject Akademi Kreyòl Ayisyen E28120 entity
Predicate shortName P43 FINISHED
Object AKA E28120 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: AKA | Statement: [Akademi Kreyòl Ayisyen, shortName, AKA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AKA
Context triple: [Akademi Kreyòl Ayisyen, shortName, AKA]
  • A. AKA chosen
    AKA is the standard abbreviation for Akademi Kreyòl Ayisyen, the official institution responsible for regulating and promoting the Haitian Creole language.
  • B. Ako
    Ako is a coastal city in southwestern Hyogo Prefecture, Japan, historically known for its salt production and the story of the Forty-seven Ronin.
  • C. Auch
    Auch is a historic town in southwestern France that serves as the capital of the Gers department and is known for its cathedral and medieval old town.
  • D. Agen
    Agen is a historic town in southwestern France known for its prunes and location between Bordeaux and Toulouse.
  • E. Akan
    Akan is a major Central Tano language spoken primarily in Ghana and parts of Côte d’Ivoire, serving as a key lingua franca and cultural language for the Akan people.
  • 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_69a498532c3481909223b74af2e578df completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c175079481909077cf11ed72d6fa completed March 1, 2026, 10:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbaf16a84819089c3473113ae70f9 completed March 7, 2026, 11:55 p.m.
Created at: March 1, 2026, 7:55 p.m.