Triple
T17561177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GDAL |
E427697
|
entity |
| Predicate | supportsStandard |
P1587
|
FINISHED |
| Object | GeoTIFF |
—
|
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: GeoTIFF | Statement: [GDAL, supportsStandard, GeoTIFF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GeoTIFF Context triple: [GDAL, supportsStandard, GeoTIFF]
-
A.
GeoTIFF
chosen
GeoTIFF is a geospatial image file format that embeds geographic metadata (such as coordinate system and projection) directly into standard TIFF raster data for use in GIS applications.
-
B.
TIF
TIF is a major annual international trade fair held in Thessaloniki, Greece, showcasing products, services, and innovations from domestic and global exhibitors.
-
C.
TIF
TIF is the IATA airport code for Taif Regional Airport, which serves the city of Taif in Saudi Arabia.
-
D.
TIF
TIF is the former New York Stock Exchange ticker symbol for Tiffany & Co., the luxury jewelry and specialty retailer.
-
E.
MrSID
MrSID is a proprietary wavelet-based image compression format commonly used for efficiently storing and distributing large geospatial raster datasets such as aerial and satellite imagery.
- 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.