Triple

T1945310
Position Surface form Disambiguated ID Type / Status
Subject Seychellois Creole E42043 entity
Predicate spokenIn P2266 FINISHED
Object Seychelles E29088 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: Seychelles | Statement: [Seychellois Creole, spokenIn, Seychelles]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seychelles
Context triple: [Seychellois Creole, spokenIn, Seychelles]
  • A. Seychelles chosen
    Seychelles is an Indian Ocean island nation off the coast of East Africa, known for its tropical beaches, coral reefs, and unique biodiversity.
  • B. Mauritius
    Mauritius is an island nation in the Indian Ocean known for its multicultural society, stable democracy, and tourism-driven economy.
  • C. Comoros
    Comoros is an island nation in the Indian Ocean off the eastern coast of Africa, known for its diverse cultural heritage and history as a former French colony.
  • D. Madagascar
    Madagascar is a large island nation in the Indian Ocean renowned for its unique biodiversity and high rate of endemic species.
  • E. Maldives
    The Maldives is a tropical island nation in the Indian Ocean renowned for its white-sand beaches, coral reefs, and luxury overwater resorts.
  • 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_69a8870e08fc8190a319cbf2600db15f completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb300af2481908ae359972843c1ef completed March 7, 2026, 5:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf046d388190a0224f76a4e13e08 completed March 9, 2026, 12:37 p.m.
Created at: March 4, 2026, 7:36 p.m.