Triple
T16491872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guanaja |
E400586
|
entity |
| Predicate | distanceToMainlandHonduras |
P5691
|
FINISHED |
| Object | about 70 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: about 70 km | Statement: [Guanaja, distanceToMainlandHonduras, about 70 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMainlandHonduras Context triple: [Guanaja, distanceToMainlandHonduras, about 70 km]
-
A.
distanceFromCentralAmerica
Indicates the measured spatial distance between a given entity and the region of Central America.
-
B.
distanceToHaiti
Indicates the measured or calculated spatial distance between a given entity or location and the country of Haiti.
-
C.
distanceFromTegucigalpa
Indicates the spatial distance between a given location and the city of Tegucigalpa.
-
D.
distanceFromManagua
Indicates the spatial distance between a given entity and the location of Managua.
-
E.
distanceFromMainland
chosen
Indicates the measured spatial separation between a location and the nearest point on the mainland.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e300a248190a3d4ca96a0a176cf |
completed | April 18, 2026, 7:09 a.m. |
| PD | Predicate disambiguation | batch_69e296902d6c8190884ddb612b8c5b36 |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:13 a.m.