Triple
T1294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | oN-Line System |
E25
|
entity |
| Predicate | inputMethod |
P91
|
FINISHED |
| Object | mouse pointing |
—
|
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: mouse pointing | Statement: [oN-Line System, inputMethod, mouse pointing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inputMethod Context triple: [oN-Line System, inputMethod, mouse pointing]
-
A.
hasInputType
chosen
Indicates that an entity takes another entity as its input type for its operation, function, or process.
-
B.
primaryLanguageOfInstruction
Indicates the language that is mainly used as the medium of teaching or instruction for a given educational context.
-
C.
languageOfWorkOrName
Indicates the language in which a work is created or a name is expressed.
-
D.
hasPrimaryFunction
Indicates that one entity serves as the main or principal function or role of another entity.
-
E.
isMechanicalOrElectronic
Indicates that something operates using mechanical components, electronic components, or a combination of both.
- 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_69a22a285828819081a58308fb963df1 |
completed | Feb. 27, 2026, 11:35 p.m. |
| NER | Named-entity recognition | batch_69a23211f05c8190b8deb03a8540d84d |
completed | Feb. 28, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69a230c2c48481908beb1db3cc9768aa |
completed | Feb. 28, 2026, 12:03 a.m. |
Created at: Feb. 27, 2026, 11:36 p.m.