The relationship between PROIEL dependency annotation … · The relationship between PROIEL dependency annotation and LFG ... taking traditional grammatical relations as primitives

Background DG and PSG The conversion Some applications

The relationship between PROIEL dependencyannotation and LFG

Dag Haug

University of Oslo

January 8

Dag Haug The relationship between PROIEL dependency annotation and LFGJanuary 8 1 / 29


Dependency Grammar

Almost a standard in computational linguistics

computationally simplegood parsers available

A natural choice for linguistic databases

fairly close to traditional school grammar → easy to annotaterelatively ‘theory-neutral’taking traditional grammatical relations as primitives



Dependency Grammar

Almost a standard in computational linguistics

computationally simplegood parsers available

A natural choice for linguistic databases

fairly close to traditional school grammar → easy to annotaterelatively ‘theory-neutral’taking traditional grammatical relations as primitives



From linguistic database to theory

On the downside, few people use DG as a linguistic theory

There is no particular theory of word order

In particular, long distance dependencies are intractable

So while DG is a reasonable format to create and store linguistic datain, we might want to (implicitly or explicitly) convert the data for ourstudies

















Lexical-Functional Grammar

Parallel architecture

Syntax is represented at two-levels: feature structure and constituentstructure

Much syntactic information (such as subcategorization frames, andeverything morphological) is lexicalised

But c-structure can also contribute information to f-structure, notablyin rigid word order languages



























What we are trying to do

From the dependency annotation in the PROIEL corpus, we want togenerate LFG representation, f-structures as well as c-structures

F-structure conversion is actually quite simple, given the similaritiesbetween DG and f-structures

Grammatical relations as primitivesNo representation of word orderPROIEL DG is already ‘fixed up’ to be closer to f-structures

C-structure conversion is more complex, but more interesting forother phrase structure based approaches

Also, having a more principled representation of word order than purelinearization is interesting for word order studies



























What do DGs represent

At the most basic level, DGs represent assymetric (head-dependent)relations between words

Typically these dependencies are labeled with grammatical relations

The analysis shows which words ‘belong together’, whether theystand together or not

The notion of syntactic category is not explicitly represented, thoughit can possibly be retrieved from morphological annotation
























What do PSGs represent

Immediate constituents, i.e.words that stand together andbelong together

Constituents are typicallylabelled with their grammaticalcategoryOften, they are enriched (e.g.X-bar theory) with a notion ofheadand a distinction betweencomplementation andadjunction

the girl killed Max




Immediate constituents, i.e.words that stand together andbelong togetherConstituents are typicallylabelled with their grammaticalcategory

Often, they are enriched (e.g.X-bar theory) with a notion ofheadand a distinction betweencomplementation andadjunction

S

Dthe

Ngirl

Vkilled

NPMax




Immediate constituents, i.e.words that stand together andbelong togetherConstituents are typicallylabelled with their grammaticalcategoryOften, they are enriched (e.g.X-bar theory) with a notion ofhead

and a distinction betweencomplementation andadjunction

S

NP

DP

the

N

girl

VP

V

killed

NP

N

Max




Immediate constituents, i.e.words that stand together andbelong togetherConstituents are typicallylabelled with their grammaticalcategoryOften, they are enriched (e.g.X-bar theory) with a notion ofheadand a distinction betweencomplementation andadjunction

S

NP

DP

the

N

girl

VP

VP

V

killed

NP

N

Max

AdvP

brutally



The choices to make

1 What are the categories?

2 What kind of projections do a category X have?

3 If a category Y depends on a category X in a dependency structure,how far should Y project before it attaches to Xs projection?

4 If a category Y depends on a category X in a dependency structure,to what position in Xs projection should Ys projection attach?

Our answers will be guided by LFG’s particular theory of c-structure,but the result should be useful for other theoretical approaches as well



The choices to make








The choices to make








The choices to make








The choices to make








Categories

Category POSAdj adjectives, attributive participles, numerals, pronounsAdv adverbsC subjunctionsConj (superfluous) conjunctionsD articleI finite verbsInt interjectionsN nouns + nominalized adjectives, numerals and pronounsP prepositionsVinf infinitive verbsVptcp participle verbs

Category inferences are configurable



Categories

Category POSAdj adjectives, attributive participles, numerals, pronounsAdv adverbsC subjunctionsConj (superfluous) conjunctionsD articleI finite verbsInt interjectionsN nouns + nominalized adjectives, numerals and pronounsP prepositionsVinf infinitive verbsVptcp participle verbs

Category inferences are configurable



What is a nominalization?

Pronouns, numerals and adjectives are ambiguous between N and Adjand are counted as N when

they have a nominal relation (subject, object, oblique, adverbial,apposition, nominal argument or partitive)

they are reflexive, personal and reciprocal pronouns, as these do nothave a determinative usethey are attributes, but genitive and the head is not genitive or has adifferent number





they have a nominal relation (subject, object, oblique, adverbial,apposition, nominal argument or partitive)they are reflexive, personal and reciprocal pronouns, as these do nothave a determinative use

they are attributes, but genitive and the head is not genitive or has adifferent number





they have a nominal relation (subject, object, oblique, adverbial,apposition, nominal argument or partitive)they are reflexive, personal and reciprocal pronouns, as these do nothave a determinative usethey are attributes, but genitive and the head is not genitive or has adifferent number



Some theoretical issues

Notice that in LFG, even functional projections should have lexicalheads

So CP and IP are projections of complementizers and finite verbs, notof V, though they belong to the functional domain of VP

Clauses with only a finite verb will only have IP, no VP

The status of DP in Greek is unclear; for simplicity I just assume DPin spec, NP.
























X-bar theory

LFG assumes a version of X-bar theory where

all categories X project two levels X’ and XPfunctional projections have specifiers, to which they assign discoursefunctionsadjunction can occur to all levels



Phrase structure rules underlying the conversionI and C have specifier positions, and so does N (but only for DPs)

Adjunction is either to X’ or to XP (appositions)

Coordination is always phrasal

A sample rule

N::phrase adjuncts:

- NP- AdjP

:specifier:- DP

:bar adjuncts:- AdjP- NP

:complements:- NP



Phrase structure rules underlying the conversionI and C have specifier positions, and so does N (but only for DPs)

Adjunction is either to X’ or to XP (appositions)

Coordination is always phrasal

A sample rule

N::phrase adjuncts:

- NP- AdjP

:specifier:- DP

:bar adjuncts:- AdjP- NP

:complements:- NP



Adjunction site

The conversion allows adjunction both to X’ and to XP - but how dowe know?

The current approach uses a mixture of category and dependencylabel

Only apos-dependents are allowed as phrasal adjunctions, if admittedby the category filter



The algorithm

1 Fix up the dependency graph so as to have a more intuitive input fora PS analysis

2 Assign a category to each node

3 Find those of the node’s dependents that should go into its phrasalprojection and add traces for the others

4 If the node projects a clause, pick up loose constituents that have notreceived head yet

5 Assign positions (phrase adjunction, specifier, bar adjunction,complement) to the nodes in the phrasal projection



The algorithm








The algorithm








The algorithm








The algorithm








Fixing up the dependency graph

DG analyses often takes the lexical word as the head, where a PSanalysis would take the functional word as the head

Shared elements in coordinations are hung on the conjunction in theDG-analysis, but on a conjunct in the PS

Otherwise we’d need X’ conjunction (possibly future work)



Fixing up the dependency graph

DG analyses often takes the lexical word as the head, where a PSanalysis would take the functional word as the head

Shared elements in coordinations are hung on the conjunction in theDG-analysis, but on a conjunct in the PS

Otherwise we’d need X’ conjunction (possibly future work)

subpred

[pred ‘men‘

],[

pred ‘women‘]

adj

{[pred ‘good’

]}

NP

NP

AdjP

Adj

good

NP

N

men

Conj

and

NP

N

women



Fixing up the dependency graphDG analyses often takes the lexical word as the head, where a PSanalysis would take the functional word as the headShared elements in coordinations are hung on the conjunction in theDG-analysis, but on a conjunct in the PSOtherwise we’d need X’ conjunction (possibly future work)

subpred

[pred ‘men‘

],[

pred ‘women‘]

adj

{[pred ‘good’

]}

N’

AdjP

Adj

good

N’

N’

N

men

Conj

and

N’

N

women



Finding the phrases

Every node in the DG heads a phrase in the PS



Finding the phrases

To find the phrases which attaches to it we look at its dependents



Finding the phrases

We map nodes to the continuous domains in their dependency graphs



Finding the phrases

For uion (7), this is [6,7,8,9]



Finding the phrases

For einai (5), it is [1] and [5,6,7,8,9]



Finding the phrases

For each such domain, we can find the words within it whosedependency graphs ‘cover’ the domain - 1 covers [1] and 7 covers[6,7,8,9]



Finding the phrases

Those which are in the same domain as their head will be the head ofcomplements - so (7) heads a complement of (5)



Finding the phrases

Those which are not in the same domain leave traces - so (5) governsthe trace of (1)



Finding the phrases

We repeat the procedure at the next level



Finding the phrases

The dependents of (2) map on to the domains [1], [3,4] and[5,6,7,8,9], which we can cover with the nodes (1), (4) and (5)



Finding the phrases

All of these are in the domain of (2), which is the whole sentence, sothey are phrasal dependents of (2)



Finding the phrases

However, (1) is not a direct dependent of (2) - so we identify it withthe trace left under (5) and resolve the trace



Finding the phrases

We only allow such resolution under nodes of category I and V



Finding the phrases

(1), (4) and (5) head projections within the projection of (2) - butwhere?



Finding the phrases

First we look for possible phrasal adjunctions (appositions) - nonehere



Finding the phrases

Next, we look for whether the leftmost constituent can be a specifier,which it can here, given our phrase structure rules



Finding the phrases

Third, we look for bar-level adjunctions, of which there are none here



Finding the phrases

Finally, we take the rest of the projections as complements under (2)



The result



What gets topicalized?

category frequencyNP 2779VptcpP 975PP 527NP[rel] 488AdvP 487CP 297NP[int] 271

category frequencyAdvP[rel] 250IP[rel] 175AdjP 171AdvP[int] 135IP 19IP[int] 5AdjP[int] 4



Types of fronted PPs

category frequency

CAUSAL 111TIME 119LOCATION 30DIRECTION 28MANNER 18SOURCE 16PURPOSE 10RECIPIENT 5TOPIC 4BENEFICIARY 2

untagged 174



Topicalizations in CP



Projectivity

Projectivity is the property of being a continous phrase (no traces)

We can distinguish two types of non-projectivity:

The displaced element occurs in a left-peripheral position(wh-movement, topicalization, relativization)The displaced element occurs ‘somewhere else’ (scrambling)

The degree of non-projectivity varies greatly across categories



Projectivity







Projectivity







Projectivity across categories

Category Wh-movement Scrambling ProjectiveCP 3 0 1351IP 28 9 10260PP 2 11 4318

VinfP 62 34 676VptcpP 9 59 2753

AdjP 3 41 331AdvP 1 12 211NP 41 212 4706

CP, IP and PP do not allow scrambling

AdvP, NP and AdjP do allow scrambling

VinfP and VptcpP behave like the AdvP, AdjP and NP



Internal subject?

If we assume that the subject can be internal to the participle phrase,there are only 12 non-projective participles phrases (6 cases ofscrambling and 6 of wh-movement) against 1625 projective ones

All of these look suspicious on closer inspection

Should we assume backward control from adjuncts instead?



Internal subject?






Internal subject?






The traditional picture



A backward control analysis



Conclusions

Dependency grammar is a interesting formalism for ‘storing’ linguisticdata

But it can and should be converted to ‘real’ linguistic theory ofvarious sorts

We have seen an algorithm to generate phrase structure fromdependencies

The phrase structure view allows more applications from boringstatistics via interesting statistics to the challenging received wisomeon Greek syntax



Conclusions







Conclusions







Conclusions







Slides available athttp://www.hf.uio.no/ifikk/proiel

Data from the PROIEL corpushttp://foni.uio.no:3000


http://www.hf.uio.no/ifikk/proiel

http://foni.uio.no:3000

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The relationship between PROIEL dependency annotation … · The relationship between PROIEL dependency annotation and LFG ... taking traditional grammatical relations as primitives