Triple
T7160885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leeward Antilles |
E166938
|
entity |
| Predicate | distanceFromSouthAmericaCoast |
P15349
|
FINISHED |
| Object | approximately 15–80 kilometers |
—
|
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 15–80 kilometers | Statement: [Leeward Antilles, distanceFromSouthAmericaCoast, approximately 15–80 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromSouthAmericaCoast Context triple: [Leeward Antilles, distanceFromSouthAmericaCoast, approximately 15–80 kilometers]
-
A.
distanceToSouthAmerica
chosen
Indicates the spatial distance between a given entity’s location and the continent of South America.
-
B.
distanceFromCoast
Indicates the measured spatial separation between a location and the nearest point on a coastline.
-
C.
distanceToPacificOcean
Indicates the physical distance between a given location or entity and the Pacific Ocean.
-
D.
distanceFromMainland
Indicates the measured spatial separation between a location and the nearest point on the mainland.
-
E.
distanceFromJuanFernandezIslands_km
Indicates the distance, measured in kilometers, between an entity and the Juan Fernández Islands.
- F. None of above.
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_69c68887a5cc8190bec0ea96227164f7 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e82ce770819081dccf7ffd50c2ab |
completed | March 27, 2026, 8:27 p.m. |
| PD | Predicate disambiguation | batch_69c6e1cd5c948190a9113b23f7308c21 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:47 p.m.