Triple

T6776790
Position Surface form Disambiguated ID Type / Status
Subject Lokono language E155577 entity
Predicate country P26 FINISHED
Object Barbados E11557 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: Barbados | Statement: [Lokono language, country, Barbados]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barbados
Context triple: [Lokono language, country, Barbados]
  • A. Barbados chosen
    Barbados is an island country in the Caribbean known for its beaches, coral reefs, and status as a popular tourist destination.
  • B. Antigua and Barbuda
    Antigua and Barbuda is a small Caribbean island nation known for its tourism-driven economy, coral reefs, and numerous white-sand beaches.
  • C. Saint Vincent and the Grenadines
    Saint Vincent and the Grenadines is a small Caribbean island nation known for its volcanic main island, numerous smaller Grenadine islands, and tourism centered on sailing and beaches.
  • D. Trinidad and Tobago
    Trinidad and Tobago is a twin-island Caribbean nation known for its rich cultural diversity, vibrant Carnival celebrations, and significant oil and natural gas resources.
  • E. Saint Lucia
    Saint Lucia is a small Caribbean island nation known for its dramatic Piton mountains, lush rainforests, and popular beach 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_69c688162bf8819088b664b5c3b5be7a completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d26725208190b64935cfd08b2aff completed March 27, 2026, 6:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c775058c388190bba04cff5dba997a completed March 28, 2026, 6:28 a.m.
Created at: March 27, 2026, 2:13 p.m.