Colazzo and Costantino (1998)

Luigi Colazzo and Marco Costantino (1998): 'Multi-user hypertextual didactic glossaries' (International Journal of Artificial Intelligence in Education, 9: 111-127).

MOTIVATION: Traditional technical glossaries (either printed or electronic, either monolingual or bilingual) suffer from a number of limitations from the perspective of the user: (a) 'loss of reading context' - the user must 'move away' from the text he is reading to look a word up in the glossary; (b) it can take a non-native speaker of the language a significant amount of time to identify the correct 'citation form' of the word he wants to look up in the dictionary; (c) glossaries are traditionally 'closed' or 'static' - it is not possible for the user to MODIFY entries or ADD new entries; (d) users who are used to working with traditional printed glossaries often fail to make use of the most useful 'search' features of electronic glossaries (i.e. they lack a sophisticated 'mental model' of the glossary - Marchionini, 1989). There are also many problems for authors of 'hypertext glossaries' (where words or phrases in the text are marked up as 'anchors' (i.e. hyperlinks) to glossary entries): (a) such annotation is very time consuming when done by hand; (b) the glossary text may not be stored in a linkable format (e.g. binary doc files); (c) if annotation is to be done automatically, then the source text needs to be morphologically analysed to identify the underlying lexemes; (d) although overlapped/embedded anchors are occasionally desirable, they are impossible to code.

Four models of hypertext glossary lookup (Black, Wright, Black and Norman, 1992): (a) TABS - the glossary entry for the selected word completely replaces the source text (it is not possible to view both at the same time, but the user had to toggle between the two tabs); (b) POPUPS - the glossary entry for the selected word effaces only a small (hopefully unimportant) part of the source text; (c) SIDEBAR - there is a permanent sidebar for displaying the selected glossary entry; (d) PREDICTIVE SIDEBAR - there is a permanent sidebar containing the glossary entries for all relevant words in the current paragraph of the source text. However, none of these models make it clear how to handle RECURSIVE lookups, i.e. where the glossary definition itself contains a word which needs to be looked up.

SOLUTIONS: (a) the glossary is indexed by 'stems' rather than particular word-forms; (b) the lookup method relies on a 'word-stemming algorithm' (what about irregular forms?); (c) links are created 'automatically' from the text to the glossary, i.e. no explicit 'anchors'; (d) the popup window containing the glossary definition should be a proper window, able to be moved around, iconised and destroyed independently of the main text window - this also provides a solution to the 'recursive lookup' problem. Also, the user can access the glossary in two distinct ways: (a) RETRIEVAL - send the glossary a text string and get back a definition; (b) BROWSING - either using an alphabetical index organised as a card file, or performing a sequential scan of entries. There is a dynamic (i.e. can be extended by the user) word-stemming algorithm, which is based on a list of all the stems in Italian, as well as the regular suffixes (but it cannot handle irregular morphology or do any POS disambiguation). The system also allows the glossary to updated by multiple users (i.e. it is a wiki).

Lisa Michaud (2008): King Alfred ...

Lisa N. Michaud (2008): 'King Alfred: a translation environment for learners of Anglo-Saxon English' (Proceedings of 3rd ACL Workshop on Innovative Use of NLP for Building Educational Applications, 19-26, link).

MOTIVATION: Learning a dead language is a much simpler task than learning a living language - the student is just learning to read/translate, rather than to listen AND speak AND read AND write. Thus, the standard approaches taken to teaching living and dead languages differ - the former focuses on developing communicative/conversational fluency and the latter syntactic accuracy. From this perspective, it appears that the somewhat primitive state-of-the-art in language technology is more appropriate for learners of dead languages.

SUMMARY: King Alfred is an online tutoring system for developing Anglo-Saxon sentence translation skills. Students have access to: (a) a morpho-syntactic scratchpad for each sentence to be translated, complete with hints and corrections; (b) a complete glossary of Anglo-Saxon word forms; and (c) a complete set of statistics about their interactions with the scratchpad.

DETAILS: The UI has three independent 'tabs': (a) the workspace; (b) the glossary; and (c) user statistics. The workspace is the core of the system:

1. The user is presented with an Anglo-Saxon sentence to translate, along with a text field to enter his/her translation (and a morpho-syntactic scratchpad - see below).
2. The user works out the translation (in consultation with the morpho-syntactic scratchpad and the glossary tab), enters it into the text field, and then presses the 'submit' button.
3. The system presents a screen containing: (a) the user's translation; (b) the instructor's model translation; (c) a 'rate your translation' bar for the user to select very poor/poor/good/very good/excellent; and (d) some tips about what morphosyntactic features the user needs to focus on (derived from his interactions with the scratchpad).
4. The user clicks the 'submit and continue' button to go to the next sentence.

The morphosyntactic scratchpad allows the user to associate morphosyntactic features with individual words. In other words, the user can guess the part-of-speech (verb, noun, adjective etc.) as well as POS-dependent grammatical features (tense, person, number etc.). The system will tell the user when he makes an incorrect guess, tell him the correct answer on request, or give him a hint.

The glossary is an alphabetised list of WORD-FORMS (i.e. not lexemes), associated with morphosyntactic information. This information is of two types: (a) lexeme-based, e.g. POS, translation, class (strong/weak), declension (1st, 2nd, etc.); and (b) form-based, e.g. number, person, tense, mood.

User statistics are derived from a complete record of the user's interactions with the system, in particular the scratchpad, across all sessions (hence the need for individual user logins). Feedback (either high-detail or low-detail) is given about the user's strengths and weaknesses in terms of particular parts-of-speech and morpho-syntactic features. In the future, this information will ideally be used to 'tailor' the order in which sentences are presented to the user.

IMPLEMENTATION: For reasons of efficient storage, the sentences and glossary are organised into a fairly complicated database structure:

The ROOTS glossary is a list of all the 'lexemes' in the glossary:

roots
  > root+ @id @orthography @pos @definition
      > feature* @name @value

The WORDS glossary is a list of all the 'word-forms' in the glossary, cross-referenced to the ROOTS glossary:

words
  > word+ @id @orthography @root-id
      > feature* @name @value

The sentences corpus is a list of all the sentences to be translated, cross-referenced to the WORDS glossary:

sentences
  > sentence+ @translation
      > word+ @word-id @translation

Our approach, which doesn not rely on any kind of automatic morphological analyser/stemmer, offers pedagogical accuracy.

INSTRUCTOR INTERFACE: There is an online interface to allow the instructor to add sentences to be translated (and hence word-forms and roots to the glossary), without needing to manipulate the database directly.

AUTOMATIC TRANSLATION EVALUATION: We intend to adapt the n-gram-based BLEU metric for translation accuracy to give users automatic feedback about the quality of their translations. Our main modification to BLEU will be to ensure that serious errors are penalised more heavily than trivial errors, and in particular that errors of morpho-syntactic parsing (e.g. mistaking a past-tense form for a present-tense form) are treated most seriously of all.

CRITIQUE: Ignores the potential for group interaction, i.e. only one user at a time can interact with the tutor. No attempt at evaluation. The section on automatic translation evaluation is purely speculative. NO NLP TECHNOLOGIES ARE USED IN THE SYSTEM.

The King Alfred homepage and documentation; Lisa Michaud's homepage; Michael Drout's homepage.

Workshops on language teaching or cultural heritage

• LaTeCH–SHELT&R'09: EACL 2009 Workshop on Language Technology and Resources for Cultural Heritage, Social Sciences, Humanities, and Education (proceedings).
• The Fourth Workshop on Innovative Use of NLP for Building Educational Applications (2009, proceedings).
• The Third Workshop on Innovative Use of NLP for Building Educational Applications (2008, proceedings).
• he Second Workshop on Building Educational Applications Using NLP (2005, proceedings)

Russell's Paradox (1901)

Where Φ denotes the axioms of Frege's naïve set theory, we can prove the following argument:

Φ :- {x|x∉x} ∈ {x|x∉x} & ~ {x|x∉x} ∈ {x|x∉x}

In other words, the axioms of Frege's naïve set theory are inconsistent.

A = {x | x ∉ x}, i.e. the set of sets which are not members of themselves.

If A ∈ A then A ∉ A.

If A ∉ A then A ∈ A.

Moral: Frege's naive set theory, based on the axioms of extensionality (two sets are equal iff they contain the same elements) and unlimited set abstraction, leads to a contradiction. Proposed solutions (1908): (a) Russell's type theory; (b) Zermelo's axiomatic set theory, which later evolved into the canonical Zermelo-Fraenkel (ZF) set theory.

Extensionality: ∀x∀y((∀z(z∈x ↔ z∈y)) ↔ x=y)

Reality consists solely of sets, along with a single primitive relation ∈ (any restrictions?). Equality is defined in terms of ∈ by means of extensionality.