Building a Discourse-annotated Dutch Text Corpus Nynke van der Vliet - - PowerPoint PPT Presentation

Building a Discourse-annotated Dutch Text Corpus

Nynke van der Vliet, Ildikó Berzlánovich, Gosse Bouma, Markus Egg, Gisela Redeker

Beyond Semantics DGfS Workshop, Göttingen, February 23-25, 2011

2

• Introduction MTO Project
• Corpus design



Text selection



Segmentation



Annotation

 Discourse structure  Genre structure  Discourse connectives  Lexical cohesion

• Preliminary results and future work

Overview

3

Modeling Textual Organization (MTO) Program

Build a Dutc tch h te text t corp rpus, annotated for discourse structure, genre structure, lexical cohesion, coreference, and discourse connectives

Project Goals:

 Investigate the genre-dependent interaction between discourse

structure and lexical cohesion (Project 1, Ildikó Berzlánovich)

 Investigate the mechanisms that establish coherence in text and

develop algorithms for discourse parsing (Project 2, Nynke van der Vliet)

• http://www.let.rug.nl/mto/

Introduction

4

• Provide a reliably annotated “gold standard” resource

covering a range of genres

• Core corpus: 80 texts (length: 190 - 400 words)
• expository texts:

20 encyclopedia texts

20 popular scientific news texts

• persuasive texts:

20 fundraising letters

20 advertisements

Corpus design

5

Text Selection (1)

Preparation: selection of text material, stripping off ‘text-external’ elements

• Exclude pictures and picture captions
• Exclude genre-specific elements that are not related to

rhetorical choices

6

Text Selection (2) Example

7

Segmentation (1)



EDU ~ simple sentence Each donation is valuable!



EDU ~ finite clause You can build with us by donating, ][ but you can also build with us literally.



EDU ~ fragment functioning as complete utterance Nice gadgets.



EDU ~ non-restrictive relative clause This gap is caused by one of the moons of Saturn, Mimas, ][ which disturbs the rings.

8

Segmentation (2)

 EDU ~ embedded discourse unit

However during the night, [ which can last for months on Mercury, ] the temperature decreases to about -185 degrees Celsius.

 EDU ~ coordinated VP

At a young age a cataract in her eye was diagnosed ][ and treated.

 EDU ~ elliptical clause

The planet turns around its axis in 58.6 days ][ and around the sun in 88.0 days.

9

Discourse Structure (1)

Rhetorical etorical Str tructure ucture Th Theory

• ry (RST)

T)

(Mann and Thompson,1988)



Full hierarchical text structure



Extended Classic RST (30 relations)



Semantic and pragmatic relations



Non-binary trees

10

(37) P.S. The enclosed cards are a thank you gift for reading my letter about the malaria epidemic in Africa. (38 ) Help us now in

• ur fight against malaria (39) by donating today (40) - within an

hour more than 120 children will die needlessly from this deadly

• disease. (41) Give generously (42) and do this today, (43) so that

we can help more children (44) before it is too late.

Discourse Structure (2)

11

Discourse Structure (3)

Multi-satellite construction (non-binary tree)tree) Restriction to binary trees yields implausible analyses

2-3 2 Help us now in our fight against malaria 3 by donating today Means 1 P.S. The enclosed cards are a thank you gift for reading my letter about the malaria epidemic in Africa. Motivation 4 - within an hour more than 120 children will die needlessly from this deadly disease. Justify 1-4

1-4 2-4 2-3 2 Help us now in our fight against malaria 3 by donating today Means 4 - within an hour more than 120 children will die needlessly from this deadly disease. Justify 1 P.S. The enclosed cards are a thank you gift for reading my letter about the malaria epidemic in Africa. Motivation 2 Help us now in our fight against malaria 3 by donating today Means 2-3 1 P.S. The enclosed cards are a thank you gift for reading my letter about the malaria epidemic in Africa. Motivation 1-3 1-4 4 - within an hour more than 120 children will die needlessly from this deadly disease. Justify

12

Move ve analysis alysis (Upton and Cohen, 2009)

• Moves = functional components in the text
• Each genre has a particular set of move types
• The moves create a linear, non-hierarchical

partition of the text

Genre structure (1)

13

Genre structure (2)

Encyclopedia texts

 Name  Define  Describe

Fundraising letters

 Get attention  Introduce the cause  Establish credentials of organization  Solicit response  Offer incentive  Reference insert  Express gratitude  Conclude with pleasantries

14

Genre structure (3)

Mapping the move structure onto RST structure

Genre structure (4)

16

Discourse Connectives (1)

Wh Why annotate notate connectives nnectives?

• At least at intra-sentential level (but probably also

across sentences), connectives should be valuable cues to coherence relations.

• Frequencies of connectives may differ between

genres and thus provide a cue for genre classification.

• Genre information may help the parser by biasing

the disambiguation of multifunctional connectives, e.g., toward a semantic meaning for expository texts and pragmatic one for persuasive texts.

17

(16) With the help of research much has already been

• achieved. (17) But to protect you and others from the

consequences of diabetes (18) more research is

• needed. (19) That is why we keep asking for your

support.

Discourse Connectives (2)

18

Lexical cohesion (1)

• Lexical cohesive items build up graph structures in the

text

• For each lexical item, lexical links to items in preceding

and following EDUs are identified

19

EDU5 [After the fo

forming ming of the sun and the solar lar system tem, our st star r began its long existence as a so-called dwarf arf st star r ] EDU6 [In the dwarf arf phase ase of its life fe, the energy that the sun gives

• ff is generated in its core through the fusion of hydrogen

into helium.] EDU7[The sun is about five billon years ]

20

Se Segmenta ntatio tion Detailed manual with rules and examples Reliability: 25% of the material, K = 0.98 (fundraising letters and encyclopedia) Cohere renc nce e analysis ysis (RST ST) Relation definitions as published on the RST website Consensus procedure: each final analysis is based on at least two independent first versions and intensive team discussion (Berzlánovich, Redeker, van der Vliet) Reliability: K = 0.88 for the spans, 0.82 for nuclearity and 0.57 for labeling

Annotations (1)

Genre e st structur ucture (move e analy lysi sis) s) Detailed manual Final analysis by consensus among two coders (Berzlánovich, Redeker) Reliability: K will be calculated on 20 % of the corpus (4 texts per genre) Lexic ical al cohes esio ion Detailed manual, training of the coders Final analysis by consensus among two coders (Berzlánovich with Rensema/ Wagenaar) Reliability: K will be calculated on 20 % of the corpus (4 texts per genre)

Annotations (2)

21

Pre relimina liminary ry re results lts on ge genre re-se sensit nsitivi ivity ty of c f cohere rence ce and co cohesion sion

(comparing encyclopedia texts and fundraising letters)

 Genre difference in coherence

• Presentational relations are much more frequent in persuasive texts

than in expository texts.

 Genre difference in cohesion

• Different discourse connectives in expository and persuasive texts.
• Systematic semantic relations are more frequent in expository texts

than in persuasive texts.

 Genre-specific interaction of coherence and cohesion

• Coherence and cohesion are closely aligned in expository texts, but

not in persuasive texts.

Coherence, Cohesion, and Genre

22

Future plans

Automatic discourse parsing

• automatic segmentation

(basic program already achieves good precision (0.72) and recall (0.75))

• determine the validity of genre, connectives, co-

reference and lexical cohesion relations as cues for the recognition of RST relations (using machine learning)

23

Thank you

24