Triple
T10330044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WFS |
E242850
|
entity |
| Predicate | supportsOperation |
P203
|
FINISHED |
| Object | GetGmlObject |
E242848
|
NE 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: GetGmlObject | Statement: [WFS, supportsOperation, GetGmlObject]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GetGmlObject Context triple: [WFS, supportsOperation, GetGmlObject]
-
A.
CityGML
CityGML is an open data model and XML-based format for storing and exchanging 3D city and landscape models, widely used in urban planning, simulation, and geographic information systems.
-
B.
OGC
OGC is the abbreviation for NASA’s Office of the General Counsel, the agency’s chief legal office responsible for providing legal advice and services.
-
C.
OGC
OGC is the Office of General Counsel within the Office of Justice Programs, providing legal advice and services on justice-related programs and policies.
-
D.
Geography Markup Language
chosen
Geography Markup Language is an XML-based standard developed by the Open Geospatial Consortium for modeling, storing, and exchanging geographic information and spatial features.
-
E.
GBXML
GBXML (Green Building XML) is an open schema used to facilitate the transfer of building information models into energy and environmental performance analysis tools.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7fb77348190ac8ff887f6f03450 |
completed | April 7, 2026, 10:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71dbc7df48190b8a11a92f946fd30 |
completed | April 9, 2026, 3:32 a.m. |
Created at: April 6, 2026, 11:52 a.m.