Triple

T216120
Position Surface form Disambiguated ID Type / Status
Subject Last Chance to See E4108 entity
Predicate setting P1957 FINISHED
Object Mauritius E28590 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: Mauritius | Statement: [Last Chance to See, setting, Mauritius]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mauritius
Context triple: [Last Chance to See, setting, Mauritius]
  • A. Mauritius chosen
    Mauritius is an island nation in the Indian Ocean known for its multicultural society, stable democracy, and tourism-driven economy.
  • B. Seychelles
    Seychelles is an Indian Ocean island nation off the coast of East Africa, known for its tropical beaches, coral reefs, and unique biodiversity.
  • C. Madagascar
    Madagascar is a large island nation in the Indian Ocean renowned for its unique biodiversity and high rate of endemic species.
  • D. 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.
  • 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_69a2573508588190b522c2476d91acfe completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25c4edfa081909fe97c86c3c7801d completed Feb. 28, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3cafa597881909ab227e02520b15c completed March 1, 2026, 5:13 a.m.
Created at: Feb. 28, 2026, 2:53 a.m.