Triple
T1459593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zipaquirá Salt Cathedral area |
E31479
|
entity |
| Predicate | distanceFromBogotá |
P29005
|
FINISHED |
| Object | about 48 kilometres |
—
|
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 48 kilometres | Statement: [Zipaquirá Salt Cathedral area, distanceFromBogotá, about 48 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromBogotá Context triple: [Zipaquirá Salt Cathedral area, distanceFromBogotá, about 48 kilometres]
-
A.
distanceToSantaMarta
Indicates the measured spatial distance between a given entity’s location and the location of Santa Marta.
-
B.
distanceFromSantiago
Indicates the spatial distance between a given entity and the location of Santiago.
-
C.
distanceFromBuenosAires
Indicates the measured distance between a given entity’s location and the city of Buenos Aires.
-
D.
distanceFromCusco
Indicates the measured spatial distance between a given location or entity and the city of Cusco.
-
E.
distanceToSantiago_km
Indicates the physical distance, measured in kilometers, between a given location and Santiago.
- 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_69a49917dfc081909acdbdf5d684f1ef |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c59c1c288190be08064f2d351b2b |
completed | March 1, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69a4c47ec5108190b1772237f2e5d90b |
completed | March 1, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69a4c52bbb748190aaa804438d31f4c2 |
completed | March 1, 2026, 11 p.m. |
Created at: March 1, 2026, 8 p.m.