Triple
T17561182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GDAL |
E427697
|
entity |
| Predicate | supportsStandard |
P1587
|
FINISHED |
| Object | WMS |
—
|
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: WMS | Statement: [GDAL, supportsStandard, WMS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WMS Context triple: [GDAL, supportsStandard, WMS]
-
A.
WMS
chosen
WMS (Web Map Service) is an Open Geospatial Consortium standard protocol for serving georeferenced map images over the internet from distributed spatial data sources.
-
B.
WMSB
WMSB is the former ICAO airport code for Sultan Abdul Aziz Shah Airport in Subang, Malaysia.
-
C.
WMSA
WMSA is the ICAO airport code for Sultan Abdul Aziz Shah Airport, a secondary airport serving the Kuala Lumpur area in Malaysia.
-
D.
WMS Industries
WMS Industries was an American gaming company best known for manufacturing slot machines and arcade games, including classic titles under the Williams and Midway brands.
-
E.
WIMM
WIMM is the ICAO airport code for Kualanamu International Airport, a major airport serving Medan and the surrounding region in North Sumatra, Indonesia.
- 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.