Triple
T8948310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gamboa |
E213278
|
entity |
| Predicate | distanceToPanamaCity |
P86493
|
FINISHED |
| Object | approximately 30 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 30 kilometers | Statement: [Gamboa, distanceToPanamaCity, approximately 30 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToPanamaCity Context triple: [Gamboa, distanceToPanamaCity, approximately 30 kilometers]
-
A.
distanceToSantaMarta
Indicates the measured spatial distance between a given entity’s location and the location of Santa Marta.
-
B.
distanceFromTegucigalpa
Indicates the spatial distance between a given location and the city of Tegucigalpa.
-
C.
distanceFromMedellín
Indicates the measured spatial distance between an entity and the city of Medellín.
-
D.
distanceFromLima
Indicates the measured distance between a given place or object and the city of Lima.
-
E.
distanceFromManagua
Indicates the spatial distance between a given entity and the location of Managua.
- 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_69ca839843408190a39069a029a89f15 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6709c7a48190ab503083a1d6a29f |
completed | April 1, 2026, 12:30 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed5267c8190a43feb2a2f3df1ec |
completed | March 31, 2026, 11:55 p.m. |
| PDg | Predicate description generation | batch_69cc60e0d7208190966797ce5f95fe49 |
completed | April 1, 2026, 12:03 a.m. |
Created at: March 30, 2026, 6:59 p.m.