Triple
T97021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scratch |
E1953
|
entity |
| Predicate | supportsExecutionModel |
P203
|
FINISHED |
| Object | in-browser execution |
—
|
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: in-browser execution | Statement: [Scratch, supportsExecutionModel, in-browser execution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsExecutionModel Context triple: [Scratch, supportsExecutionModel, in-browser execution]
-
A.
supportsFeature
chosen
Indicates that one entity provides, enables, or is compatible with a particular feature or capability of another.
-
B.
hasSupported
Indicates that one entity has provided assistance, endorsement, or backing to another entity, either materially, emotionally, or through advocacy.
-
C.
executedWith
Indicates that an action or process was carried out using, accompanied by, or in conjunction with a specified tool, method, or participant.
-
D.
supportsPolicy
Indicates that one entity endorses, backs, or is in favor of a particular policy or set of policies.
-
E.
supportsActivity
Indicates that one entity provides the necessary conditions, resources, or environment for another entity’s activity to occur or be sustained.
- 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a250cb400c8190b56343bbe19b48c7 |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ebd19c48190bab291fea0ecc0c2 |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.