Du TAL au TIL
It proposes a novel paradigm for NLP to address variable human knowledge, but is incremental as it builds on existing ideas without specific applications.
The paper introduces Interactive Natural Language Processing (INLP) as a new approach to bridge the gap between human knowledge and goals, arguing it is feasible and cost-effective.
Historically two types of NLP have been investigated: fully automated processing of language by machines (NLP) and autonomous processing of natural language by people, i.e. the human brain (psycholinguistics). We believe that there is room and need for another kind, INLP: interactive natural language processing. This intermediate approach starts from peoples' needs, trying to bridge the gap between their actual knowledge and a given goal. Given the fact that peoples' knowledge is variable and often incomplete, the aim is to build bridges linking a given knowledge state to a given goal. We present some examples, trying to show that this goal is worth pursuing, achievable and at a reasonable cost.