Triple

T6619017
Position Surface form Disambiguated ID Type / Status
Subject John A. Osborne Airport E149627 entity
Predicate serves P98 FINISHED
Object Montserrat E17737 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: Montserrat | Statement: [John A. Osborne Airport, serves, Montserrat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montserrat
Context triple: [John A. Osborne Airport, serves, Montserrat]
  • A. Montserrat chosen
    Montserrat is a small Caribbean island and British Overseas Territory known for its volcanic activity and lush, mountainous landscape.
  • B. Monte
    Monte was the nickname of Monte Irvin, a Hall of Fame American baseball player renowned as one of the early Black stars to break Major League Baseball’s color barrier.
  • C. Serra
    Serra is a Spanish surname most famously associated with Junípero Serra, the 18th-century Franciscan friar who founded several missions in what is now California.
  • D. Morne la Selle
    Morne la Selle is the highest mountain in Haiti, located in the southern part of the country.
  • E. Mount Aigaleo
    Mount Aigaleo is a low mountain range in the Attica region of Greece, west of Athens, known for its historical and strategic significance overlooking the ancient battlefield of Salamis.
  • 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_69c687ed8a9c81908bb671717cb192ef completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6af5ca97481909f8a7dc47249b4d3 completed March 27, 2026, 4:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6eee8740881908b4fafb12db6b7f3 completed March 27, 2026, 8:56 p.m.
Created at: March 27, 2026, 1:58 p.m.