Triple

T584934
Position Surface form Disambiguated ID Type / Status
Subject Leeward Islands E15137 entity
Predicate hasMajorIsland P756 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: [Leeward Islands, hasMajorIsland, Montserrat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montserrat
Context triple: [Leeward Islands, hasMajorIsland, Montserrat]
  • A. Montserrat chosen
    Montserrat is a small Caribbean island and British Overseas Territory known for its volcanic activity and lush, mountainous landscape.
  • B. 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.
  • C. Mount Pico
    Mount Pico is a prominent stratovolcano on Pico Island in the Azores and the highest peak in Portugal.
  • D. Mount Nivea
    Mount Nivea is a prominent mountain peak that forms the highest point in the remote South Orkney Islands of the Southern Ocean.
  • E. Nevis
    Nevis is a small volcanic island in the Caribbean known for its lush landscapes, historic plantations, and tranquil beaches.
  • 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_69a4935783b8819082b77726ec10cc42 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49b9874c88190bd1e08d4689ea124 completed March 1, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69a518c44ef0819088048289ed31246f completed March 2, 2026, 4:57 a.m.
Created at: March 1, 2026, 7:33 p.m.