Languages are not only means of expression, but also vehicles of
thought, allowing us to discover new ideas (brainstorming) or clarify existing ones by refining,
expanding, illustrating more or less well specified thoughts. Of course, all this must be learned, and to
this end we need resources, tools and knowledge on how to use them.
Knowledge can be encoded at various levels of abstractions, considering
different units (words, sentences, texts). While semantic maps represent words and their
relations at a micro-level, schematic maps (tree banks, pattern libraries) represent them combined,
in larger chunks (macrolevel). We all are familiar with microscopes, maps, and navigational tools, and
we normally associate them with professions having little to do with NLP. I will argue during my
talk that this does not need to be so. Methaphorically speaking, we do use the very same tools to
process language, regardless of the task (analysis vs. generation) and the processor (machine vs. human
brain).
Dictionaries are resources, but they can also be seen as microscopes as they reveal in more
detail the hidden meanings, nutshelled in a word. This kind of information
display can be achieved nowadays by a simple mouse-click, even for languages whose script we
cannot read (e.g. oriental languages for most Europeans). A corpus query system like Sketch Engine
can reveal additionally very precious information: a word’s grammatical and collocational
behaviour in texts.
Unlike inverted spyglasses, which reduce only size, macroscopes are tools that allow us to
get the great picture. Even though badly needed, they are not yet available in
hardware stores, but they do exist in some scientists’ minds. They are known under the headings of
pattern recognition, feature detectors, etc. The resulting abstractions, models or blueprints
(frames, scripts, patterns) are useful for a great number of tasks. I will illustrate this point for patterns
via two examples related to realtime language production and foreign
language learning (acquisition of fluency via a selfextending speakable phrasebook).
Semantic maps (wordnets,
thesauri, ontologies, encyclopedias) are excellent tools for organizing words and knowledge in a huge multidimensional meaning space.
Nevertheless, in order to be truly useful, i.e. to guarantee access to the stored and desired information,
maps are insufficient — we also need some navigational tool(s). To illustrate this point I will
present some of my ongoing work devoted to the building of a lexical compass. The assumption is that
people have a highly connected conceptual-lexical network in their mind. Finding a word amounts thus to
entering the network at any point by giving a related word (source word) and to follow then the
links (associations) until one has reached the target word. To allow for this kind of navigation,
we try to build an association matrix that contains on one axis the target words and on the other the
trigger words. Once built, this kind of tool should allow the user to navigate quickly and naturally, by
starting from anywhere, to reach in very few steps the desired word, with the search being based on
whatever knowledge is available at the onset of search.
Short bio: Prof. Michael Zock,
H.PHD, is research director at CNRS, LIF (Laboratory of Fundamental
Informatics). His research interests lie in cognitive science and
language production, including the development of tools to assist
language production (L1 + L2) and its acquisition, and understanding and
simulating the cognitive processes underlying
discourse planning (automatic creation of an outline) and word access.
He is the author of hundreds of international publications in the field.
