Triple
T32782370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rémire-Montjoly |
E838391
|
entity |
| Predicate | distanceToCayenne |
P72796
|
FINISHED |
| Object | approximately 10 km southeast |
—
|
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 10 km southeast | Statement: [Rémire-Montjoly, distanceToCayenne, approximately 10 km southeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToCayenne Context triple: [Rémire-Montjoly, distanceToCayenne, approximately 10 km southeast]
-
A.
distanceFromCayenne
chosen
Indicates the measured distance between a given entity or location and the place named Cayenne.
-
B.
distanceFromPortOfSpain
Indicates the measured distance between a given location and the city of Port of Spain.
-
C.
distanceFromCharlotteAmalie
Indicates the measured distance between a given location and Charlotte Amalie.
-
D.
distanceFromCaribbeanCoast
Indicates the measured distance between a location and the coastline of the Caribbean Sea.
-
E.
distanceFromPortLouis
Indicates the measured distance between a given location and Port Louis.
- 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_69f3493b83f48190be335cd42465cecf |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:14 a.m.