Triple
T18799390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | xarray |
E459722
|
entity |
| Predicate | supportsPlotting |
P33227
|
FINISHED |
| Object | quicklook plots via Matplotlib |
—
|
LITERAL 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: quicklook plots via Matplotlib | Statement: [xarray, supportsPlotting, quicklook plots via Matplotlib]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsPlotting Context triple: [xarray, supportsPlotting, quicklook plots via Matplotlib]
-
A.
supportsPlotDevice
Indicates that one entity provides narrative justification, reinforcement, or facilitation for the use or effectiveness of a particular plot device in a story.
-
B.
hasPlot
Indicates that an entity (such as a narrative work) possesses or is associated with a specific storyline or sequence of events.
-
C.
plotter
Indicates that one entity is a device or tool used by another entity to produce precise graphical or plotted output.
-
D.
hasCharting
chosen
Indicates that one entity provides or supports charting or graphical data visualization capabilities for another entity.
-
E.
supportsModelingOf
Indicates that one entity provides the capability or functionality needed to represent, simulate, or model another entity or process.
- F. None of above.
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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a02273b481909bc250144a0ace32 |
completed | April 20, 2026, 3:40 a.m. |
| PD | Predicate disambiguation | batch_69e48d16dd34819096e096d0c0e4c15c |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:53 a.m.