Triple
T11278639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bonaire National Marine Park |
E267003
|
entity |
| Predicate | locatedIn |
P40
|
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: [Bonaire National Marine Park, locatedIn, Bonaire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bonaire Context triple: [Bonaire National Marine Park, locatedIn, 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 small Caribbean island that was once a Dutch West India Company colony and is now a special municipality of the Netherlands known for its rugged volcanic terrain and marine biodiversity.
-
E.
Saba
Saba is a consumer electronics brand known for products such as televisions and audio equipment, historically popular in Europe.
- 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e967ebb4819080b09ed3cec44e77 |
completed | April 9, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e58b2614308190b9de143e3a80bfc0 |
completed | April 20, 2026, 2:10 a.m. |
Created at: April 8, 2026, 9:31 p.m.