I wonder about the legitimacy of using the terms "POS tagging", "Chunking", "Disambiguation" and "Categorization" to describe an activity that doesn't include writing code and database queries, or interacting with the NLP algorithm and database directly.
More specifically, let's suppose I use the following tools:
an "Annotator" for analyzing the input text (e.g. sentences copypasted from online newspapers) and choose and save proper values as regards to "POS" of tokens and words, "Words"(entities and collocations) and "Chunk". Tokens are already detected by default. I have to decide which words are entities and/or collocations or not and their typology, though. May the performed tasks be called "POS tagging", "Chunking" and "support to categorization"?
A knowledge base, for searching and choosing the proper synsets of the lemmas and assigning them to the words analyzed in the previous Annotation tool. May such a task be called "Disambiguation"?
A graphical user interface which shows how the NLP analyzes by default the input texts as regards to Lemmas, POS, Chunks, Senses, entities, domains, main concepts, dependency tree, in order to make analyses consistent with it.
If I want to define these activities in a few words, "Machine Learning annotation" may be the most correct.
But what if I want to be more specific? I don't know whether or not the terms "POS tagging", "Chunking", "Disambiguation" and "Support to categorization" may be appropriate for they generally come within "programming contexts", as far as I know. In other terms, do they involve writing algorithms and programming or are they / may they be referred to the "less-technical" activities described above?