Triple
T11796956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bonaire |
E280524
|
entity |
| Predicate | distanceToVenezuelaCoast |
P101624
|
FINISHED |
| Object | approximately 80 km |
—
|
LITERAL 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: approximately 80 km | Statement: [Bonaire, distanceToVenezuelaCoast, approximately 80 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToVenezuelaCoast Context triple: [Bonaire, distanceToVenezuelaCoast, approximately 80 km]
-
A.
distanceToHaiti
Indicates the measured or calculated spatial distance between a given entity or location and the country of Haiti.
-
B.
distanceToSouthAmerica
Indicates the spatial distance between a given entity’s location and the continent of South America.
-
C.
distanceFromPortOfSpain
Indicates the measured distance between a given location and the city of Port of Spain.
-
D.
distanceFromCoast
Indicates the measured spatial separation between a location and the nearest point on a coastline.
-
E.
distanceToMexicoBorder
Indicates the measured or estimated distance between a given location or entity and the border of Mexico.
- F. None of above. chosen
Provenance (4 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_69d6ab258b808190b1735835c841e3a4 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5a1cda0819092d66a82fd882786 |
completed | April 10, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69d8a2491f048190853239bc05090bf4 |
completed | April 10, 2026, 7:10 a.m. |
| PDg | Predicate description generation | batch_69d8a43cc0c881909fed7cd759fe90b1 |
completed | April 10, 2026, 7:18 a.m. |
Created at: April 8, 2026, 9:42 p.m.