Triple
T17598551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tkinter |
E428634
|
entity |
| Predicate | supportsEventModel |
P36418
|
FINISHED |
| Object | event loop |
—
|
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: event loop | Statement: [Tkinter, supportsEventModel, event loop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsEventModel Context triple: [Tkinter, supportsEventModel, event loop]
-
A.
supportedEvent
chosen
Indicates that an entity is capable of recognizing, handling, or being associated with a particular type of event.
-
B.
supportsEventSeries
Indicates that an entity provides the necessary functionality or resources to host, manage, or accommodate a recurring series of related events.
-
C.
supportsModelType
Indicates that an entity is compatible with, or can operate using, a specified model type.
-
D.
supportsModelingOf
Indicates that one entity provides the capability or functionality needed to represent, simulate, or model another entity or process.
-
E.
supportsContributionModel
Indicates that one entity enables or is compatible with a particular model or framework for making contributions (such as donations, content, or resources).
- 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46c474e5481909d2736241b592dab |
completed | April 19, 2026, 5:46 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fff0348190b899a32da537eaca |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:51 a.m.