Triple
T96997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scratch |
E1953
|
entity |
| Predicate | usesCodeRepresentation |
P103
|
FINISHED |
| Object | drag-and-drop blocks |
—
|
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: drag-and-drop blocks | Statement: [Scratch, usesCodeRepresentation, drag-and-drop blocks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesCodeRepresentation Context triple: [Scratch, usesCodeRepresentation, drag-and-drop blocks]
-
A.
hasRepresentationIn
chosen
Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or context.
-
B.
codeType
Indicates the classification or category assigned to a particular code within a coding or encoding system.
-
C.
codifiedIn
Indicates that something is formally recorded, defined, or established within a specific document, code, or legal/institutional text.
-
D.
numericCode
Indicates that an entity is associated with a specific numerical identifier or classification code.
-
E.
usesComputationMethod
Indicates that an entity performs its processing or decision-making by applying a specified computational method or algorithm.
- 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.