The NITE XML Toolkit

Jean Carletta

University of Edinburgh

HCRC Language Technology Group

NITE XML Toolkit

http://www.ltg.ed.ac.uk/NITE

Edinburgh, Stuttgart, DFKI

• NOT the NITE Workbench for Windows from the University of Southern Denmark

The NITE XML Toolkit

• integrated support for creating and searching different kinds of annotation on the same speech and video data

• data format that allows for distributed data production

• some standard GUIs, data utilities• support for writing high quality hand-

annotation tools for new tasks quickly

NXT corpus design

• data model is multi-rooted tree with arbitrary graph structure over the top– each node has one set of children, multiple parents

• annotations often naturally map to a tree– design task is deciding where trees intersect

• NXT can represent arbitrary graphs but the more the data has this character, the less useful the search is

Only configuration needed to:

• search/index data in NXT format

• display data in a standardized (ugly) way

• (NXT 1.3.0) do an increasing number of "usual" annotation tasks– dialogue act– named entity– time-stamped labelling like The Observer

Programming tailored interfaces

• development time is 1.5 days - 2 weeks depending on – how clear the spec is– complexity of the interface– familiarity with Swing

• NXT 1.3.0 will include middleware reducing this and making typical program ~200 lines of code

GUI Demos

Recommended Data Paths (1)

• Transcribe data outside NXT– Transcriber or multi-channel version of it

• Create timestamped base layers either in NXT or in your favourite other tool– The Observer, Anvil, TASX, EventEditor

Recommended Data Paths (2)• Use NXT as a reference storage format for shared data

– everyone contributes data to a CVS repository from which different versions of the corpus can be built

• work in NXT natively when sensible – to create annotations structured over base layers– search/index

• Use NXT's generic utilities (or roll your own) to export data, run it through some machine process, and re-import the result– POS, morphology, automatic annotation based on statistical

model

Up-translation into NXT format

• existing translations for several common tools

• take .5-4 days to write, depending on– documentation of input format– complexity of mapping

• complete lattice output of SR takes thought

Why NXT?

• best support for distributed creation of hand-annotations structured over transcription

• best search facility for integrated data set

any other approach takes more dedicated development time; main task here is corpus design and up-translation

Reported Problems at Installation

• won't run – zip file truncated during download– forgot to set classpath– don't have Java

• can't get signal to play– video codec not installed/not registered in JMF– format not supported by JMF

• no one thing to run

Reserves

extract from Bdb001.A.words.xml

<w nite:id="Bdb001.w.1,342" starttime="356.39" endtime="" c="W">time</w> <w nite:id="Bdb001.w.1,343" starttime="" endtime="" c="HYPH">-</w> <w nite:id="Bdb001.w.1,344" starttime="" endtime="356.59" c="W">line</w>

extract from Bdb001.A.speech-quality.xml<speechquality nite:id="Bdb001.emphasis.16" type="emphasis"> <nite:child href="Bdb001.A.words.xml#id(Bdb001.w.1,342)..id(Bdb001.w.1,344)" /> </speechquality>

Stand-off XML

GUI support (low level)

• a central clock keeps data displays/signal in synch• pre-defined display widgets for text areas, trees,

grids• interfaces that displays can implement

– in order to stay synchronized with clock

– to allow search results to be highlighted

• predefined GUIs for displaying a dialogue, searching a corpus that work for anything

Metadata file

• Equivalent to set of DTDs for the XML files plus:– connections between the files– list of "observations" (coded dialogues/group

discussions/texts)– catalog for finding signals and data on disk

Data Handling API

• Load corpus or meaningful subparts of a corpus (down to individual XML file)

• Data access, traversal, and manipulation with most important validation done on-line

• Serialization with choice of standoff syntax• Off-line procedure for full validation

All data is held in memory; "dump-n-reload" memory management planned

Query/search

Simple example query

($w word)($r reference): ($w@POS = “NN”) && ($r ^ $w)

Match pairs of words and referring expressions where the word’s part of speech is NN and the word is in the referring expression.

General features of the language

• Match variable by no type, single type, or disjunctive type

• The usual boolean operators plus some syntactic sugar, like ->

• Quantifiers forall and exists (which do not contribute to the n-tuple returned)

Attribute and content tests

• Existence

• Ordering and equality against numbers and strings

• Match to regexp

Temporal tests

• Whether data object is timed

• Start or end time before, after, same as given time

• Same temporal extent, inclusion, abutment, overlap temporal precedence

• Start and end times treated as special attributes, for finer comparisons

Structural tests

• Identity• Dominance (traceable through 0 to n

children)• Precedence (before in some tree ordering)• Relationship via a role, which must be

named

• Some distance/tree-limited functionality

Complex queries

• Evaluate first query, and carry over resulting bindings when evaluating second

• Result is a tree

• Any n-tuples from the first query that have no matches for the second are removed

• Faster to run, more intuitive to write, easier to perform frequency counts

Example complex query

($a w):(TEXT($a) ~ /th.*/)::($s speechquality):($s ^ $a) && ($s@type="emphasis")

 • Find instances of words starting with “th”• For each find instances of speech quality tags of

type "emphasis" that dominate the word• Discard words that are not dominated by at least

one such tag

Uses for queries

• Exploring the data

• Basic frequency counts

• Verifying data quality

• Indexing complexes for further use

• Finding things for screen rendering in GUI

Warts

• Currently builds in-memory representation of complete data set being loaded– work-arounds: process one dialogue at a time, don't load the

annotations you don't need– lazy loading and better memory management under development

• In large, distributed corpora, pain to assemble the subcorpus you want– build mechanism under development

• Some useful things missing from query language– arithmetic– distance-limited precedence