Triple
T1647961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VBA |
E35623
|
entity |
| Predicate | canAutomate |
P30852
|
FINISHED |
| Object | workbooks and worksheets in Excel |
—
|
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: workbooks and worksheets in Excel | Statement: [VBA, canAutomate, workbooks and worksheets in Excel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canAutomate Context triple: [VBA, canAutomate, workbooks and worksheets in Excel]
-
A.
canMake
Indicates that one entity has the ability or capacity to create, produce, or assemble another entity.
-
B.
canUse
Indicates that one entity has the ability, permission, or suitability to make use of another entity or resource.
-
C.
canBe
Indicates that one entity has the potential, permission, or capability to become, perform as, or be classified as another entity.
-
D.
canLiaiseWith
Indicates that one entity is able or permitted to communicate and coordinate directly with another entity for collaboration or information exchange.
-
E.
canBePerformed
Indicates that a particular action or activity is possible to carry out under given conditions or by a specified agent.
- F. None of above. chosen
Provenance (4 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_69a8860568888190a32cd9f70acbba42 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaa0fbe984819084f8daee81ca9b67 |
completed | March 6, 2026, 9:40 a.m. |
| PD | Predicate disambiguation | batch_69a907ce4dd881909168a1e99505d4ec |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a949509d508190a3a35554996823de |
completed | March 5, 2026, 9:13 a.m. |
Created at: March 4, 2026, 7:29 p.m.