Triple
T17561179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GDAL |
E427697
|
entity |
| Predicate | supportsStandard |
P1587
|
FINISHED |
| Object | GeoJSON |
—
|
NE NERFINISHED |
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: GeoJSON | Statement: [GDAL, supportsStandard, GeoJSON]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GeoJSON Context triple: [GDAL, supportsStandard, GeoJSON]
-
A.
GeoJSON
chosen
GeoJSON is a widely used JSON-based format for encoding a variety of geographic data structures, including points, lines, polygons, and their associated attributes.
-
B.
TopoJSON
TopoJSON is a geospatial data format that extends GeoJSON by encoding topology, allowing for more efficient storage and shared boundaries between geographic features.
-
C.
ESRI Shapefile
ESRI Shapefile is a widely used geospatial vector data format for geographic information system (GIS) software, commonly employed to store and exchange map features and their associated attributes.
-
D.
WKT
WKT (Well-Known Text) is a text-based markup language used to represent vector geometry objects such as points, lines, and polygons in geographic information systems.
-
E.
KML
KML (Keyhole Markup Language) is an XML-based file format used to display geographic data and annotations in mapping applications such as Google Earth and Google Maps.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e456267e208190a1238fbe1a535bb0 |
completed | April 19, 2026, 4:12 a.m. |
Created at: April 10, 2026, 5:50 a.m.