Triple
T4798899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pukará de Quitor |
E106783
|
entity |
| Predicate | distanceFromNearestTown |
P3883
|
FINISHED |
| Object | about 3 kilometers from San Pedro de Atacama |
—
|
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 3 kilometers from San Pedro de Atacama | Statement: [Pukará de Quitor, distanceFromNearestTown, about 3 kilometers from San Pedro de Atacama]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromNearestTown Context triple: [Pukará de Quitor, distanceFromNearestTown, about 3 kilometers from San Pedro de Atacama]
-
A.
hasNearbyTown
chosen
Indicates that one location has a town situated close to it in geographic proximity.
-
B.
distanceFromDowntown
Indicates the physical distance between a given location and the central downtown area.
-
C.
distanceFromHanaTown (miles)
Indicates the number of miles separating a given place or entity from Hana Town.
-
D.
hasNearestLargerSettlement
Indicates that one settlement is associated with the geographically closest settlement that is larger in size or population.
-
E.
nearestTownCenter
Indicates that one location is the closest town center to another specified point or area.
- 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_69bd43f6a1e08190bf0a372bfc336ee5 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6b40c29c8190adab3503f8ba0145 |
completed | March 20, 2026, 3:44 p.m. |
| PD | Predicate disambiguation | batch_69bd622f88188190a51d52ccfad3d2dd |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:22 p.m.