Triple
T27238081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BZE |
E687120
|
entity |
| Predicate | distanceToBelizeCityKilometers |
P168015
|
FINISHED |
| Object | approximately 15 |
—
|
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 | Statement: [BZE, distanceToBelizeCityKilometers, approximately 15]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBelizeCityKilometers Context triple: [BZE, distanceToBelizeCityKilometers, approximately 15]
-
A.
distanceFromBelizeCity
chosen
Indicates the spatial distance separating a given place or object from Belize City.
-
B.
distanceFromBelizeMainland
Indicates the measured spatial distance separating a given entity from the mainland territory of Belize.
-
C.
distanceFromTegucigalpa
Indicates the spatial distance between a given location and the city of Tegucigalpa.
-
D.
distanceFromSantoDomingo
Indicates the spatial distance between a given entity and the location of Santo Domingo.
-
E.
distanceFromSanSalvador
Indicates the measured distance between an entity and the location of San Salvador.
- 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_69ef355547408190b5ca0d777c65040a |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69ff1ba8694481909ceb36f26ca85612 |
completed | May 9, 2026, 11:34 a.m. |
| PD | Predicate disambiguation | batch_69ff1b27f0f08190a9e74308c5b3d1ba |
completed | May 9, 2026, 11:31 a.m. |
Created at: April 27, 2026, 10:35 a.m.