Triple
T13827873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flamingo International Airport |
E332299
|
entity |
| Predicate | locatedOnIsland |
P970
|
FINISHED |
| Object | Bonaire |
E53516
|
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: Bonaire | Statement: [Flamingo International Airport, locatedOnIsland, Bonaire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bonaire Context triple: [Flamingo International Airport, locatedOnIsland, Bonaire]
-
A.
Bonaire
chosen
Bonaire is a Caribbean island and special municipality of the Netherlands, known for its exceptional marine biodiversity and world-class scuba diving and snorkeling sites.
-
B.
Curaçao
Curaçao is a Dutch Caribbean island known for its colorful colonial architecture, vibrant coral reefs, and distinctive blue liqueur.
-
C.
Aruba
Aruba is a small Dutch Caribbean island renowned for its white-sand beaches, warm climate, and tourism-driven economy.
-
D.
Saba
Saba is a consumer electronics brand known for products such as televisions and audio equipment, historically popular in Europe.
-
E.
Saba
Saba was an ancient South Arabian kingdom, often associated with the biblical land of Sheba, renowned for its wealth, incense trade, and advanced irrigation systems in what is now Yemen.
- 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_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02970df88190a1bf35dffd131d9d |
completed | April 14, 2026, 9:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcb648146c8190842a3da4e4c0e217 |
completed | May 7, 2026, 3:56 p.m. |
Created at: April 9, 2026, 10:13 p.m.