Triple
T17561102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MapServer |
E427696
|
entity |
| Predicate | implementsStandard |
P1587
|
FINISHED |
| Object | WFS |
—
|
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: WFS | Statement: [MapServer, implementsStandard, WFS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WFS Context triple: [MapServer, implementsStandard, WFS]
-
A.
WFS
chosen
WFS (Web Feature Service) is an OGC standard web service that provides access to and manipulation of geographic features over the internet in vector form.
-
B.
WSF
WSF is the vehicle registration code used on license plates for the Burgenlandkreis district in the German state of Saxony-Anhalt.
-
C.
WSF
WSF is the commonly used abbreviation for Washington State Ferries, the largest ferry system in the United States serving routes across Puget Sound and nearby waterways.
-
D.
FWS
FWS is a U.S. federal financial aid program that provides part-time jobs to eligible college students to help them pay for educational expenses.
-
E.
FWSB
FWSB is the commonly used abbreviation for the Roman Catholic Diocese of Fort Wayne–South Bend in Indiana.
- 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.