Triple
T27071407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bassin Bleu |
E685334
|
entity |
| Predicate | approximateTravelTimeFromJacmel |
P182214
|
FINISHED |
| Object | about 45–60 minutes by car plus hike |
—
|
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 45–60 minutes by car plus hike | Statement: [Bassin Bleu, approximateTravelTimeFromJacmel, about 45–60 minutes by car plus hike]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateTravelTimeFromJacmel Context triple: [Bassin Bleu, approximateTravelTimeFromJacmel, about 45–60 minutes by car plus hike]
-
A.
distanceToPort-au-Prince
Indicates the spatial distance between a given location and the city of Port-au-Prince.
-
B.
distanceFromPortLouis
Indicates the measured distance between a given location and Port Louis.
-
C.
distanceToHaiti
Indicates the measured or calculated spatial distance between a given entity or location and the country of Haiti.
-
D.
distanceFromCharlotteAmalie
Indicates the measured distance between a given location and Charlotte Amalie.
-
E.
distanceFromSantoDomingo
Indicates the spatial distance between a given entity and the location of Santo Domingo.
- 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_69ef14843b1481909d828b3d5a44550a |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f7886be6d8819095ec62e4f2cee858 |
completed | May 3, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69f7841440f48190b4346c08855951d2 |
completed | May 3, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69f7886b27f08190ab4580f949222c93 |
completed | May 3, 2026, 5:39 p.m. |
Created at: April 27, 2026, 8:28 a.m.