Corpus Annotation @ ICE-corpora.net

The corpora in ICE are being annotated at various levels to enhance their value in linguistic research. These levels are

Textual Markup
Wordclass Tagging
Syntactic Parsing

Textual Markup
In written texts, features of the original layout are marked, including sentence and paragraph boundaries, headings, deletions, and typographic features.

Spoken texts are transcribed orthographically, and are marked for pauses, overlapping strings, discourse phenomena such as false starts and hesitations, and speaker turns.

The markup manual is available here.

Wordclass Tagging
ICE texts are automatically tagged for wordclass by the ICE Tagger, developed by Sean Wallis at the Survey of English Usage, University College London. This assigns wordclass tags to each lexical item in the corpus. The tagset has been developed especially for ICE, and is largely based on Quirk et al (1985) A Comprehensive Grammar of the English Language. An example of a grammatically tagged sentence is shown below:

Each	PRON(univ,sing)
of	PREP(ge)
these	PRON(dem,plu)
is	V(cop,pres)
the	ART(def)
responsibility	N(com,sing)
of	PREP(ge)
one	NUM(card,sing)
person	N(com,sing)

The tagging manual is available here

Syntactic Parsing
Every sentence in the corpus is analysed at phrase, clause, and sentence level, and the analysis is shown in the form of a parse tree:

For more details about the grammatical annotation, see the Quick Guide to the ICE-GB Grammar (on the UCL server).

The parse trees are edited and corrected, if necessary, using a version of ICECUP, a dedicated syntactic tree editor and retrieval system which has been developed specifically for ICE.

In addition to the annotation levels above, some ICE teams will digitize their sound recordings, aligning them with the orthographic transcriptions. The British team has completed the digitization and alignment stage. The American team is adding detailed prosodic annotations to their transcriptions of spoken texts.
The ICE-Ireland team have produced a version of their corpus with pragmatic annotation.