Annotation of Cohesive Devices

Representation

There following Structural Attributes:

lexicalcohesion
lexicalcohesion_id            [A]
lexicalcohesion_distance      [A]
lexicalcohesion_lexical_type  [A]
lexicalcohesion_distance_type [A]
lexicalcohesion_lexical_chain [A]

lexicalcohesion_id: is an ID of a markable

lexicalcohesion_distance: is supposed to be a distance between various anaphors (but wasn’t annotated in most cases and needed to be calculated)

lexicalcohesion_lexical_type: indicates the semantic relation an item has

lexicalcohesion_distance_type: is not annotated, is always immediate

lexicalcohesion_lexical_chain: has the value ‘set_ZAHL’ and indicates the ID of chains

Querying lexical cohesion

• every token which belong to a member of lexical chain (unsorted, unclassified):

[lexicalcohesion];

• every member of every chain (one and multiword):

/region[lexicalcohesion];

STATISTICS:

to get the number of elements:

size Last;

At the moment, we have some elements which are there but do not belong to any chain. To sort them out, please use the following command:

<lexicalcohesion>[_.lexicalcohesion_lexical_chain!="none|empty"]+</lexicalcohesion>;

If you want to query the first element in the chain (for instance to count the number of chains):

<lexicalcohesion>[_.lexicalcohesion_lexical_chain!="none|empty"&_.lexicalcohesion_lexical_type="first|none"]+</lexicalcohesion>;

size Last;

To query all elements of chains except for the fist elements, use:

<lexicalcohesion>[_.lexicalcohesion_lexical_chain!="none|empty"&_.lexicalcohesion_lexical_type!="first|none"]+</lexicalcohesion>;

size Last;

To export a table with the number of first elements (chains) per register:

tabulate Last match text_register> "|sorttabulate|sort -k 2|cat > /data/projects/steiner/gecco/results/lexical-cohesion/chains/first-register-SUBCORPUS.csv

To export a table with the number of first elements (chains) per text:

tabulate Last match text_id> "|sorttabulate|sort -k 2|cat > /data/projects/steiner/gecco/results/lexical-cohesion/chains/first-text-SUBCORPUS.csv

To assess the distributions of semantic relations:

group Last match lexicalcohesion_lexical_type;

To export a table (with semantic relations) sorted according to registers:

tabulate Last match text_register, match lexicalcohesion_lexical_type > "|sorttabulate|sort -k 2|cat > /data/projects/steiner/gecco/results/lexical-cohesion/chains/relations-register-SUBCORPUS.csv"

To export a table (with semantic relations) sorted according to texts:

tabulate Last match text_id, match lexicalcohesion_lexical_type > "|sorttabulate|sort -k 2|cat > /data/projects/steiner/gecco/results/lexical-cohesion/chains/relations-text-SUBCORPUS.csv"

To extract the information on chains size, we would need some post-processing steps for average sizes. But we can already extract information on chains size per text:

[_.lexicalcohesion_lexical_chain!="none|empty"]+</lexicalcohesion>;

tabulate Last match text_id, match lexicalcohesion_lexical_chain> "|sorttabulate|sort -k 2|cat > /data/projects/steiner/gecco/results/lexical-cohesion/chains/chains-text-SUBCORPUS.csv"

To assess certain chains, you could use the information from the extraction on chain size and analyse, for instance, the longest chains. here is an example:

In the text EO_ESSAY_007, we have a chain which consists of more than 30 elements, so we have a closer look at it:

[_.lexicalcohesion_lexical_chain="set_3"&_.text_id="EO_ESSAY_007"]+</lexicalcohesion>;

Representation

There following Structural Attributes:

mention
mention_type         [A]
mention_func         [A]
mention_chain_id     [A]
mention_cohesive     [A]
mention_anaphor      [A]
mention_problematic  [A]

antecedents have the following attribute-values:

chain_id="set_ZAHL" problematic="yes|no" cohesive="anaphoric" func="modifier" type="dem" antecedent="none"

anaphors have the following attribute-values:

chain_id="set_ZAHL" problematic="yes|no" cohesive="anaphoric" func="es/it-endophoric/exophoric|modifier|person/possessive-endophoric|article|head|general|particular|local|temporal|pronadv" type="pers|dem|comp" antecedent="np|pronominal|fact-s|other|event-vp|is-a"

anaphors without antecedents (e.g. comparative) have the following attribute-values:

chain_id="empty" problematic="yes|no" cohesive="none" func="es/it-endophoric/exophoric|modifier|person/possessive-endophoric|article|head|general|particular|local|temporal|pronadv" type="pers|dem|comp"

referring expressions have the following subtypes (saved as values of mention_type):

• pers
• dem
• comp

And the subtypes or functions are (saved as values of mention_func):

pers in EO

• personal
• possessive
• it-endophoric
• it-exophoric

pers in GO

• personal
• possessive
• es/it-endophoric
• es/it-exophoric

dem

• head
• modifier
• local
• temporal
• pronadv
• correlat-pronadv

comp

• particular
• general

All referring expressions have annotations on the features of the antecedent they refer to (saved as values of mention_antecedent):

• np
• fact-s
• pronominal
• other
• event-vp
• is-a

Querying coreference

• every token which belong to reference (unsorted, unclassified):

[mention];

• every member of every chain (one and multiword):

/region[mention];

STATISTICS:

to get the number of elements:

size Last;

to get the types of referring expressions:

group Last match mention_type;

to get the functions of referring expressions:

group Last match mention_func;

NOTE!

querying demonstrative referring expressions for German, please exclude one function:

mention_func="correlat-pronadv"

For this use for example the following query:

[_.mention_type!="correlat-pronadv"];

to get the list of referents (antecedents):

/region[mention]::match.mention_antecedent="none";

to get the information on the number of chains per text:

tabulate Last match text_id > "|sorttabulate>/data/projects/steiner/gecco/results/reference-chains.csv"

to get the list of anaphors:

/region[mention]::match.mention_antecedent!="none";

to get the types of antecedents of the queried anaphors:

group last match mention_antecedent;

in EO-GECCO2013, ETRANS-GECCO, GO-GECCO2013, GTRANS-GECCO, EO-SPOKEN2013 and GO-SPOKEN2013

Assessing chunk information

run a query to extract all referring expressions:

[_.mention_antecedent!="none"] expand to mention;

count grammatical function of these:

group Last match NP_gf;

group Last match NP_gf1;

you need to repeat grouping as many times, as many NP levels there are.

Another possibility:

tabulate Last match NP_gf;

or

tabulate Last match NP_gf, match NP_gf1;

etc.

for INFORMATION ON GRAMMATICAL FUNCTIONS SEE INFORMATION ON CHUNKS for [[howtos:extractions:eo-gecco&#grammatical_functions|EO]] and [[howtos:extractions:go-gecco#grammatical_functions|GO]]

Representation

• nominal substitution (expressed with //one, einen//, etc. )
• verbal substitution (expressed with //do so, tun//, etc.)
• clausal substitution (expressed with //so//)

saved as the following Structural Attributes:

substitution
substitution_type

Querying

• any token (unsorted, unclassified):

[substitution];

or for the whole structure:

/region[substitution];

or:

<substitution>[]+</substitution>;

STATISTICS:

size Last;

group Last match substitution;

group Last match substitution_type;

with Register information:

group Last match text_register by match substitution;

group Last match text_register by match substitution_type;

• substitution types (concrete Querying):

[_.substitution_type="nominal"];

[_.substitution_type="verbal"];

[_.substitution_type="clausal"];

STATISTICS

size Last;

EXAMPLE of querying all types of substitution in EO-GECCO:

EO-GECCO;

<substitution>[]+</substitution>;

group Last match text_register by match substitution;

tabulate Last match substitution_type, match text_register > "|sorttabulate > substitution.csv";

Representation

conj
conj_type
conj_func
conj_problematic

subjunct
connect
adverbial

additive
adversative
causal
temporal
modal

Querying

• Any token

[conj];

• all conjunctions (unsorted, unclassified):

<conj>[]+[]*</conj>;

/region[conj];

• activate the borders of syntactic types of conjunctions:

show +conj_type;

• activate the borders of semantic types of conjunctions:

show +conj_func

• concrete Querying (one element only):

<conj>[_.conj_type="connect"]</conj>;

<conj>[_.conj_type="subjunct"]</conj>;

<conj>[_.conj_type="adverbial"]</conj>;

• concrete Querying (one and multi-word element):

<conj>[_.conj_type="connect"]+[_.conj_type="connect"]*</conj>;

<conj>[_.conj_type="subjunct"]+[_.conj_type="subjunct"]*</conj>;

<conj>[_.conj_type="adverbial"]+[_.conj_type="adverbial"]*</conj>;

• same for semantic types:

<conj>[_.conj_func="additive"]+[_.conj_func="additive"]*</conj>;

<conj>[_.conj_func="adversative"]+[_.conj_func="adversative"]*</conj>;

<conj>[_.conj_func="causal"]+[_.conj_func="causal"]*</conj>;

<conj>[_.conj_func="temporal"]+[_.conj_func="temporal"]*</conj>;

<conj>[_.conj_func="modal"]+[_.conj_func="modal"]*</conj>;

STATISTICS:

group Last match conj_type;

group Last match conj_func;

tabulate Last match conj_type, match conj_func > "|sorttabulate> /data/projects/steiner/gecco/results/conj.csv";

EXAMPLE - For statistics of different semantic types in different registers in EO

EO-GECCO;

<conj>[]+[]*</conj>;

group Last match conj_func by match text_register;

tabulate Last match conj_func, match text_register > "|sorttabulate > conj_func-eo.csv";

Representation

• nouns (general)

saved as the following Structural Attributes:

noun
noun_type

And the types are (saved as values of reference_type):

• general

Querying

• Any token

[noun];

• or:

/region[noun];

• activate the borders of types:

show +noun_type

STATISTICS:

size Last;

group Last match noun_type;

• For statistics of different semantic types in different registers

group last match noun_type by text_register;

tabulate Last match lemma, match noun_type, match text_register > "|sorttabulate > generalnoun-CORPUS.csv";

Representation

• ellipsis

saved as the following Structural Attributes:

ellipsis
ellipsis_problematic [A]
ellipsis_func        [A]
ellipsis_type        [A]
ellipsis_antecedent  [A]
ellipsis_item        [A]
ellipsis_id          [A]

The items are (saved as values of ellipsis_item):

unspecified
antecedent
clause-internal antecedent
antecedent_ambig

The antecedents can be (saved as values of ellipsis_antecedent) either empty or some markables

The possible types are saved as ellipsis_type and include:

texttype
split
nominal
nonclausal
clausal
verbal
other
mixed_nominal+verbal/clausal
yes_no

The possible functions (saved as ellipsis_func):

non-cohesive
cohesive
clause-internal

If there were problems in annotation, e.g. disambiguation, unclear context, etc. the ellipsis were annotated with the category of problematic (ellipsis_problematic) with the values ‘yes’ or ‘no’

NOTE* that we were able to annotate triggers only, not empty items. So the annotated structure indicate that the ellipsis follows.

antecedents are recognisable as follows:

id="markable_ZAHL" type="texttype|split|nominal|nonclausal|clausal|verbal|other|mixed_nominal+verbal/clausal|yes_no" func="cohesive|non-cohesive|clause-internal" item="antecedent|antecedent_ambig|clause-internal antecedent" cohesive="yes|no" antecedent="empty" problematic="yes|no"

anaphors are recognisable as follows: id="markable_ZAHL" type="texttype|split|nominal|nonclausal|clausal|verbal|other|mixed_nominal+verbal/clausal|yes_no" func="endophoric|exophoric" item="unspecified" antecedent="markable_ZAHL" problematic="yes|no"

Querying

• All ellipsis

/region[ellipsis];

• all cohesive ellipsis (anaphors of elliptical chains):

[_.ellipsis_func="cohesive"&_.ellipsis_item="unspecified"] expand to ellipsis;

• all antecedents of cohesive elliptical chains:

[_.ellipsis_func="cohesive"&_.ellipsis_item="antecedent|antecedent_ambig"] expand to ellipsis;

• activate the borders of types:

show +ellipsis_type

• activate other structures:

show +ellipsis_ATTRIBUTE

• It is possible to restrict the search to certain registers, for example, in this case for essays and speeches.

/region[ellipsis]::match.text_register="ESSAY|SPEECH";

• It is also possible to exclude certain types from the query, for example, extract non-problematic cases only:

/region[ellipsis]::match.ellipsis_problematic="no";

• To restrict your search to certain types of ellipsis, use the same type of query:

/region[ellipsis]::match.ellipsis_ATTRIBUTE="VALUE";

STATISTICS:

size Last;

group Last match ellipsis_type;

• For statistics of different types in different registers

group last match ellipsis_type by text_register;

tabulate Last match ellipsis_type, match text_register > "|sorttabulate > ellipsis-CORPUS.csv";

• Collect all statistics on the extracted ellipsis

tabulate Last match ellipsis_item, ellipsis_type, ellipsis_func, match text_register > "|sorttabulate > ellipsis-CORPUS.csv";