Triple
T18143083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Natural Language Input for a Computer Problem-Solving System |
E434311
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | computational linguistics paper |
C28998
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: computational linguistics paper Context triple: [Natural Language Input for a Computer Problem-Solving System, instanceOf, computational linguistics paper]
-
A.
natural language processing paper
chosen
A natural language processing paper is a scholarly work that presents methods, experiments, and findings on computational techniques for analyzing, understanding, or generating human language.
-
B.
linguistics journal
A linguistics journal is a periodical publication that presents peer-reviewed research articles, reviews, and scholarly discussions on the scientific study of language and its structure, use, and development.
-
C.
natural language processing research program
A natural language processing research program is an organized, systematic effort to develop and study computational methods that enable machines to understand, generate, and interact using human language.
-
D.
natural language processing conference
A natural language processing conference is a formal gathering where researchers, practitioners, and industry professionals present, discuss, and advance methods and applications for computational understanding and generation of human language.
-
E.
linguistic corpus
A linguistic corpus is a large, structured collection of authentic texts or transcribed speech used for analyzing language patterns, usage, and structure.
- F. None of above.
Provenance (1 batch)
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_69d8b90aac308190801e2c57d8c5bfe5 |
completed | April 10, 2026, 8:47 a.m. |
Created at: April 10, 2026, 10:29 a.m.