Triple
T21636234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ebène, Mauritius |
E533966
|
entity |
| Predicate | distanceFromPortLouis |
P145343
|
FINISHED |
| Object | approximately 15 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 kilometers | Statement: [Ebène, Mauritius, distanceFromPortLouis, approximately 15 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromPortLouis Context triple: [Ebène, Mauritius, distanceFromPortLouis, approximately 15 kilometers]
-
A.
distanceFromPortOfSpain
Indicates the measured distance between a given location and the city of Port of Spain.
-
B.
distanceFromMahé
Indicates the measured spatial distance between a given entity’s location and Mahé.
-
C.
distanceToPort-au-Prince
Indicates the spatial distance between a given location and the city of Port-au-Prince.
-
D.
distanceFromCayenne
Indicates the measured distance between a given entity or location and the place named Cayenne.
-
E.
distanceFromCharlotteAmalie
Indicates the measured distance between a given location and Charlotte Amalie.
- 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_69e0c465ae7481908577b7209fdb2a77 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef538ddb088190a3cba6fdc84c0ae8 |
completed | April 27, 2026, 12:16 p.m. |
| PD | Predicate disambiguation | batch_69e69677b9c48190bf81f795aa8ad74e |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69cb4bcbc8190a4fc2d508df107be |
completed | April 20, 2026, 9:37 p.m. |
Created at: April 16, 2026, 6:35 p.m.