Triple
T2175216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GML |
E48510
|
entity |
| Predicate | hasVersion |
P455
|
FINISHED |
| Object | GML 2.0 |
E48510
|
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: GML 2.0 | Statement: [GML, hasVersion, GML 2.0]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GML 2.0 Context triple: [GML, hasVersion, GML 2.0]
-
A.
GML
chosen
GML (Geography Markup Language) is an XML-based standard developed by the Open Geospatial Consortium for modeling, transporting, and storing geographic information and spatial features.
-
B.
Global C platform (second generation)
The Global C platform (second generation) is Ford’s compact vehicle architecture underpinning small vans and cars like the Ford Transit Connect, designed to deliver improved efficiency, safety, and driving dynamics.
-
C.
RPL programming language
RPL is a stack-based, reverse Polish Lisp-like programming language developed by Hewlett-Packard for its graphing calculators, combining features of RPN and structured programming.
-
D.
GSL
GSL is the vehicle registration code assigned to cars registered in a specific district of Poland’s Pomeranian Voivodeship.
-
E.
GROM
GROM is Poland’s elite special operations unit renowned for high-risk counterterrorism, hostage rescue, and unconventional warfare missions.
- 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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbece30888190936853740ff6cb02 |
completed | March 7, 2026, 5:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae5d9eff988190a02734bd73616cba |
completed | March 9, 2026, 5:41 a.m. |
Created at: March 4, 2026, 7:45 p.m.