Proceedings of EACL '99 
Parsing with an Extended Domain of Locality 
John Carroll, Nicolas Nicolov, Olga Shaumyan, Martine Smets g¢ David Weir 
School of Cognitive and Computing Sciences 
University of Sussex 
Brighton, BN1 9QH, UK 
Abstract 
One of the claimed benefits of Tree Ad- 
joining Grammars is that they have an 
extended domain of locality (EDOL). We 
consider how this can be exploited to 
limit the need for feature structure uni- 
fication during parsing. We compare 
two wide-coverage lexicalized grammars 
of English, LEXSYS and XTAG, finding 
that the two grammars exploit EDOL in 
different ways. 
1 Introduction 
One of the most basic properties of Tree Adjoining 
Grammars (TAGS) is that they have an extended 
domain of locality (EDOL) (Joshi, 1994). This 
refers to the fact that the elementary trees that 
make up the grammar are larger than the cor- 
responding units (the productions) that are used 
in phrase-structure rule-based frameworks. The 
claim is that in Lexicalized TAGS (LTAGs) the el- 
ementary trees provide a domain of locality large 
enough to state co-occurrence relationships be- 
tween a lexical item (the anchor of the elemen- 
tary tree) and the nodes it imposes constraints 
on. We will call this the extended domain of 
locality hypothesis. 
For example, wh-movement can be expressed 
locally in a tree that will be anchored by a verb 
of which an argument is extracted. Consequently, 
features which are shared by the extraction site 
and the wh-word, such as case, do not need to be 
percolated, but are directly identified in the tree. 
Figure 1 shows a tree in which the case feature 
at the extraction site and the wh-word share the 
same value) 
1The anchor, substitution and foot nodes of trees 
are marked with the symbols o, $ and *, respectively. 
Words in parenthesis are included in trees to provide 
examples of strings this tree can derive. 
Much of the research on TAGS can be seen as 
illustrating how its EDOL can be exploited in vari- 
ous ways. However, to date, only indirect evidence 
has been given regarding the beneficial effects of 
the EDOL on parsing efficiency. The argument, 
due to Schabes (1990), is that benefits to parsing 
arise from lexicalization, and that lexicalization is 
only possible because of the EDOL. A parser deal- 
ing with a lexicalized grammar needs to consider 
only those elementary structures that can be as- 
sociated with the lexical items appearing in the 
input. This can substantially reduce the effective 
grammar size at parse time. The argument that 
an EDOL is required for lexicalization is based on 
the observation that not every set of trees that 
can be generated by a CFG can be generated by 
a lexicalized CFG. But does the EDOL have any 
other more direct effects on parsing efficiency? 
On the one hand, it is a consequence of the 
EDOL that wide-coverage LTAGs are larger than 
their rule-based counterparts. With larger ele- 
mentary structures, generalizations are lost re- 
garding the internal structure of the elementary 
trees. Since parse time depends on grammar size, 
this could have an adverse effect on parsing effi- 
ciency. However, the problem of grammar size in 
TAG has to some extent been addressed both with 
respect to grammar encoding (Evans et al., 1995; 
Candito, 1996) and parsing (Joshi and Srinivas, 
1994; Evans and Weir, 1998). 
On the other hand, if the EDOL hypothesis holds 
for those dependencies that are being checked by 
the parser, then the burden of passing feature val- 
ues around during parsing will be less than in a 
rule-based framework. If all dependencies that 
the parser is checking can be stated directly within 
the elementary structures of the grammar, they 
do not need to be computed dynamically during 
the parsing process by means of feature percola- 
tion. For example, there is no need to use a slash 
feature to establish filler-gap dependencies over 
unbounded distances across the tree if the EDOL 
217 
Proceedings of EACL '99 
S 
$ NP\[¢~ :,¢¢\] S (whom) 
SNP VP 
e 
Figure 1: Localizing a filler-gap dependency 
makes it possible for the gap and its filler to be 
located within the same elementary structure. 
This paper presents an investigation into the ex- 
tent to which the EDOL reduces the need for fea- 
ture passing in two existing wide-coverage gram- 
mars: the XTAG grammar (XTAG-Group, 1995), 
and the LEXSYS grammar (Carroll et al., 1998). 
It can be seen as an evaluation of how well these 
two grammars make use of the EDOL hypothesis 
with respect to those dependencies that are being 
checked by the parser. 
2 Parsing Unification-Based 
Grammars 
In phrase-structure rule-based parsing, each rule 
corresponds to a local tree. A rule is applied to 
a sequence of existing contiguous constituents, if 
they are compatible with the daughters. In the 
case of context-free grammar (CFG), the compat- 
ibility check is just equality of atomic symbols, 
and an instantiated daughter is merely the corre- 
sponding sub-constituent. 
However, unification-based extensions of 
phrase-structures grammars are used because 
they are able to encode local and non-local 
syntactic dependencies (for example, subject- 
verb agreement in English) with re-entrant 
features and feature percolation, respectively: 
Constituents are represented by DAGS (directed 
acyclic graphs), the compatibility check is unifi- 
cation, and it is the result of each unification that 
is used to instantiate the daughters. Graph uni- 
fication based on the UNION-FIND algorithm has 
time complexity that is near-linear in the number 
of feature structure nodes in the inputs (Huet, 
1975; Ait-Kaci, 1984); however, feature structures 
in wide-coverage grammars can contain hundreds 
of nodes (see e.g., HPSG (Pollard and Sag, 1994)), 
and since unification is a primitive operation the 
overall number of unification attempts during 
parsing can be very large. Unification therefore 
has a substantial practical cost. 
Efficient graph unification must also ensure that 
it does not destructively modify the input struc- 
tures, since the same rule may be used several 
times within a single derivation, and also the 
same constituent may be used within different 
partial analyses with features instantiated in dif- 
ferent ways. Copying input feature structures 
in their entirety before each unification would 
solve this problem, but the space usage renders 
this approach impractical. Therefore, various 
'quasi-destructive' algorithms (Karttunen, 1986; 
Kogure, 1990; Tomabechi, 1991) and algorithms 
using 'skeletal' DACS with updates (Pereira, 1985; 
Emele, 1991) have been proposed, which at- 
tempt to minimize copying. But even with good 
implementations of the best of these improved 
algorithms, parsers designed for wide-coverage 
unification-based phrase-structure grammars us- 
ing large HPSG-style feature graphs spend around 
85-90% of their time unifying and copying feature 
structures (Tomabechi, 1991), and may allocate in 
the region of 1-2 Mbytes memory while parsing 
sentences of only eight words or so (Flickinger, 
p.c.). Although comfortably within main mem- 
ory capacities of current workstations, such large 
amounts of short-term storage allocation overflow 
CPU caches, and storage management overheads 
become significant. 
In the case of unification-based LTAG the situa- 
tion is even more problematic. Elementary struc- 
tures are larger than productions, and the poten- 
tial is that the parser will have to make copies 
of entire trees and associated feature structures. 
Furthermore, the number of trees that an LTAG 
218 
Proceedings of EACL '99 
S S 
$ NP\[.g~ : Eli VP SNP\[ w:3~g l VP Lcase : nomj 
oV\[~g,:m\] SNP oV\[.g,: 3~g\] SNP 
I 
loves 
Figure 2: Unanchored and anchored trees localizing subject/verb agreement 
parser must consider tends to be far larger than 
the number of rules in a corresponding phrase- 
structure grammar. On the other hand, the EDOL 
has the potential to eliminate some or all of feature 
percolation, and in the remainder of this section, 
we explain how. 
An LTAG consists of a set of unanchored trees 
such as the one shown on the left of Figure 2. 
This shows a tree for transitive verbs where sub- 
ject/verb agreement is captured directly with re- 
entrancy between the value of agr feature struc- 
tures at the anchor (verb) node and the subject 
node. Notice the re-entrancy between the anchor 
node and the substitution node for the subject. 
However these are not the trees that the parser 
works with; the parser is given trees that have 
been anchored by the morphologically analysed 
words in the input sentence. For example, the tree 
shown on the right is the result of anchoring the 
tree shown on the left with the word loves. An- 
choring instantiates the agr feature of the anchor 
node as 3sg which has the effect (due to the re- 
entrancy in the unanchored tree) of instantiating 
the agr feature at the subject node as 3sg. 
Anchored elementary trees are translated by the 
parser into a sequence of what we will refer to 
as parser actions. For example, once the tree 
shown on the right of Figure 2 has been asso- 
ciated with the word loves in the input, it can 
be recognized with a sequence of parser actions 
that involve finding a NP constituent on the right 
(corresponding to the object), possibly perform- 
ing adjunctions at the VP node, and then finding 
another NP constituent on the left (corresponding 
to the subject). We say that the two NP substitu- 
tion nodes and the VP node are the sites of parser 
actions in this tree. Problems arise, and the EDOL 
hypothesis is violated, when there is a dependence 
between different parser actions. 
The EDOL hypothesis states that elementary 
trees provide a domain of locality large enough to 
state co-occurrence relationship between the an- 
chor of the tree and the nodes it imposes con- 
straints on. If all dependencies relevant to the 
parser can be captured in this way then, once an 
elementary tree has been anchored by a particu- 
lar lexical item, the settings of feature values at 
all of the dependent nodes will have been fixed, 
and no feature percolation can occur. Each uni- 
fication is a purely local operation with no reper- 
cussions on the rest of the parsing process. No 
copying of feature structures is required, so mem- 
ory usage is greatly reduced, and complex quasi- 
destructive algorithms with their associated com- 
putational overheads can be dispensed with. 
Note that, although feature percolation is elim- 
inated when the EDOL hypothesis holds, the fea- 
ture structure at a node can still change. For ex- 
ample, substituting a tree for a proper noun at 
the subject position of the tree in Figure 2 would 
cause the .feature structure at the node for the 
subject to'include pn:+. This, however, does not 
violate the EDOL hypothesis since this feature is 
not coreferenced with any other feature in the tree. 
3 Analysis of two wide-coverage 
grammars 
As we have seen, the EDOL of LTAGs makes it pos- 
sible, at least in principle, to locally express de- 
pendencies which cannot be localized in a CFG- 
based formalism. In this section we consider two 
existing grammars: the XTAG grammar, a wide- 
coverage LTAG, and the LEXSYS grammar, a wide- 
coverage D-Tree Substitution Grammar (Rambow 
et al., 1995). For each grammar we investigate the 
extend to which they do not take full advantage 
of the EDOL and require percolation of features at 
parse time. 
There are a number of instances in which depen- 
dencies are not localized in the XTAG grammar, 
most of which involve auxiliary trees. There are 
219 
Proceedings of EACL '99 
three types of auxiliary trees: predicative, modi- 
fier and coordination auxiliary trees. In predica- 
tive auxiliary trees the anchor is also the head of 
the tree and becomes the head of the tree resulting 
from the adjunction. In modifier auxiliary trees, 
the anchor is not the head of the tree, and the sub- 
tree headed by the anchor usually plays a role of 
adjunct in the resulting tree. Coordination auxil- 
iary trees are similar to modifier auxiliary trees in 
that they are anchored by the conjunction which 
is not the head of the phrase. One of the conjoined 
nodes is a foot node, the other one a substitution 
node. 
3.1 Modifier Auxiliary Trees 
In modifier auxiliary trees -- an example of which 
is shown in Figure 32 -- the feature values at the 
root and foot nodes are set by the node at which 
the auxiliary tree is adjoined, and have to be per- 
colated between the foot node and the root node. 
The LEXSYS grammar adopts a similar account of 
modification. 
From a parsing point of view, this does not re- 
sult in the need for feature percolation: only the 
foot node of the modifier tree is the site of a parser 
action, and the root node is ignored by the process 
that interprets the tree for the parser. 
3.2 Coordination Auxiliary Trees 
An example of an XTAG coordination auxiliary 
tree is shown on the left of Figure 4. This case is 
different from the modification case since features 
of the substitution node have to be identical to fea- 
tures of the foot node (which wiIl match those at 
the adjunction site). From a parsing point of view 
these nodes are both the sites of actions, resulting 
in the need for feature percolation. For example, 
for the NP coordination tree shown in Figure 4, 
if one of the conjuncts is a wh-phrase, the other 
conjunct must be a wh-phrase too, as in who or 
what did this? but *John and who did this? The 
wh-feature has to be percolated between the two 
nodes on each side of the conjunction. 
In the LEXSYS grammar, a coordination tree is 
anchored by a head of the tree, not by the con- 
junction. To illustrate (see the tree on the right 
of Figure 4), N P-coordination trees are anchored 
by a noun, and features such as wh and case are 
ground during anchoring. As a result, there is no 
need for passing of these features in the coordina- 
tion trees of the LEXSYS grammar. 
2All examples relating to the XTAG grammar come 
from the XTAG report (XTAG-Group, 1995). They 
have been simplified to the extent that only details 
relevant to the discussion are included. 
As for agreement features, there are two cases 
to consider: if the conjunction is and, the number 
feature of the whole phrase is plural; if the con- 
junction is or, the number feature is the same as 
the last conjunct's (XTAG-Group, 1999). In both 
the XTAG and LEXSYS grammars, this is achieved 
by having separate trees for each type of conjunc- 
tion. 
3.3 Predicative Auxiliary Trees 
In the XTAC grammar, subject raising and aux- 
iliary verbs anchor auxiliary trees rooted in VP, 
without a subject3; they can be adjoined at the 
VP node of any compatible verb tree. With this 
arrangement, subject-verb agreement must be es- 
tablished dynamically. The agr feature of the NP 
subject must match the agr feature of whichever 
VP ends up being highest at the end of the deriva- 
tion. In Figure 5, the bought tree has been an- 
chored in such a way that adjunction at the VP 
node is obligatory, since a matrix clause cannot 
have mode:ppart. 4 When the tree for has is ad- 
joined at the VP node the agr features of the sub- 
ject will agree with those of bought. The feature 
structure at the root of the tree for has is unified 
with the upper feature structure at the VP node 
of the tree for bought, and the feature structure 
at the foot of the tree for has is unified with the 
lower feature structure at the VP node of the tree 
for bought. The foot node of the has tree is the VP 
node on the frontier of the tree. Note that even 
after the tree has been anchored, re-entrancy of 
features occurs in the tree. 
Thus, there are two sites in the tree for bought 
(the subject NP node and the VP node) at which 
parser actions will take place (substitution and 
adjunction, respectively) such that a dependency 
between the values of the features at these two 
nodes must be established by the parser. 
The situation is similar for case assignment 
(also shown in the Figure 5): the value of a fea- 
ture ass-case (the assign case feature) on the high- 
est VP is coreferred with the value of the feature 
case on the subject NP. For finite verbs, the value 
of the feature ass-case is determined by the mode 
of the verb. For infinitive verbs, case is assigned 
in various ways, the details of which are not rele- 
vant to the discussion here. The subject is in the 
nominative case if the verb is finite, and in the 
accusative otherwise. As with the agr feature, the 
value of the case feature cannot be instantiated 
3To allow for long distance dependency, subject 
raising verbs must anchor an auxiliary tree, with iden- 
tical root and foot nodes, a VP. 
4Unifying the two feature structures at the VP node 
would cause a matrix clause to have mode:ppart. 
220 
Proceedings of EACL '99 
Nm 
o Adj • NI~ 
I 
red 
Figure 3: XTAG example of modifying auxiliary tree 
f * NP\[=~ m~\] oConj 
. NP\[ Wh: 
I 
and 
Np\[ ~h:- 1 
s N p 
,t. Conj NP 
oNF h: Lcase .'--nora/ace\] 
apples 
Figure 4: Coordination in XTAG (left) and LEXSYS (right) 
in the anchored elementary tree of the main verb 
because auxiliary verb trees can be adjoined. 
The same observations apply to the XTAG treat- 
ment of copula with predicative categories such as 
an adjective. As shown in Figure 6, these pred- 
icative AP trees have a subject but no verb; trees 
for raising verbs or the copula can be adjoined 
into them. As in the previous example, the agr 
features of the verb and subject cannot be instan- 
tiated in the elementary tree because the verb and 
its subject are not present in the same tree. 
From the examples we have seen, it appears that 
the XTAG grammar does not take full advantage 
of the EDOL with respect to a number of syntactic 
features, for example those relating to agreement 
and case. The LEXSYS grammar takes a rather dif- 
ferent approach to phenomena that XTAG handles 
with predicative auxiliary trees. 
The LEXSYS grammar has been designed to lo- 
calize syntactic dependencies in elementary trees. 
As in the XTAC grammar, unbounded dependen- 
cies between gap and filler are localized in elemen- 
tary trees; but unlike the XTAG grammar, other 
types of syntactic dependencies, such as agree- 
ment, are also localized. All finite verbs, including 
auxiliary and raising verbs, anchor a tree rooted 
in S, and thus are in the same tree as the subject 
with which they agree. An example involving fi- 
nite verbs is shown in Figure 7. Since verb trees 
cannot be substituted between the subject and the 
verb, the agr feature can be grounded when ele- 
mentary trees are anchored, rather than during 
the derivation. The case feature of the subject 
can be specified even in the unanchored elemen- 
tary tree: in trees for finite verbs the subject has 
nominative case; in trees for for ... to clauses it 
has accusative case. 
As can be seen from the tree on the right of 
Figure 7, subject raising and auxiliary verbs are 
rooted in S and take a VP complement. So the 
sentence He seems to like apples is produced by 
substituting a VP-rooted tree for to like into a tree 
for seems. 
Thus, for all three trees shown in Figure 7, 
once anchoring has taken place, all of the syn- 
tactic features being checked by the parser are 
grounded. Hence, the parser does not have to 
check for dependencies between the parser actions 
taking place at different sites in the tree. 
3.4 Semantic Dependencies 
There are many examples where the ×TAG gram- 
mar, but not the LEXSYS grammar, localizes se- 
mantic dependencies: for example, dependencies 
221 
Proceedings of EACL '99 
S\[modo: \]\] 
$ NP \[:g:o::\[~\] vP L:o%: T° mJ ~.~~rnode : ppart\] 
I 
bought 
fagr : 3sg "1 .ore / 
L : o:Th :omj., oo d 
has 
Figure 5: XTAG example with a raising verb 
S \[mode : I~1\] 
,I.NP - VP \[m°~ 
oV\[mooo:,o \] ,vP I I 
I e o Adv is I 
upset 
Figure 6: XTAG example of a predicative adjective 
between an adjective and its subject. As shown in 
Figure 6, in XTAG the predicative adjective and its 
subject are localized in the same elementary tree, 
and selectional restrictions can be locally imposed 
by the adjective on the subject without the need 
for feature percolation. On the other hand, in the 
LEXSYS grammar, the dependency between upset 
and he in he looks upset could not be checked dur- 
ing parsing without the use of feature passing be- 
tween the subject and AP node of the tree in the 
middle of Figure 7. 
3.5 Percolation of Features in LEXSYS 
This section considers a limited number of cases 
where it appears that it is not possible to set 
all syntactic features by anchoring an elementary 
tree. 
When two nodes other than the anchor of the 
tree are syntactically dependent, feature values 
may have to be percolated between these nodes 
(the anchor does not determine the value of these 
features). For example, in English adjectives that 
can have S subjects determine the verb form of the 
subject. Hence, in Figure 8, the verb form feature 
of the subject is not determined by the anchor 
of the tree (the verb) but by the complement of 
the anchor (the adjective). The verb form feature 
must therefore be percolated from the adjective 
phrase to the subject. 
The XTAG grammar localizes this dependency 
(see Figure 6). However, as we have seen, agree- 
ment features are not localized in this analysis. 
The problem then is that it does not seem to be 
possible to localize all syntactic features in this 
case. 
Feature percolation is also required in the 
LEXSYS grammar for prepositional phrases which 
contain a wh-word, because the value of the wh 
feature is not set by the anchor of the phrase (the 
preposition) but by the complement (as in these 
reports, the wording on the covers of which has 
caused so much controversy, are to be destroyed5 ). 
The value of the feature wh is set by the N P- 
complement, and percolated to the root of the PP. 
4 Conclusions 
In XTAG both syntactic and semantic features are 
considered during parsing, whereas in the LEXSYS 
5Example borrowed from Gazdar et al. 1985. 
222 
Proceedings of EACL '99 
S S 
$ NP \[~": 3,, \] VP $ NP \[~e: 3'~ml VP Lcase : nomj 
Vi ''g' : 3'g \] SNP o V L,.,o,~ : i,,,~j o \['g': 3,g l ,L AP Lmocle : indJ I 
I 
likes looks 
S 
SNP\[:~ 
<>V\[~g, : 3,g \] Lmode : indj .,~ VP \[mode : inf\] 
seems 
Figure 7: LEXSYS example for case and agr features 
S 
SS\[mo  
oV ragr : 3sg \] $ J~P \[subj : mode : \[~\]\] j Lmode : indJ 
looks 
Figure 8: LEXSYS example for subject/adjective syntactic dependency 
system only syntactic dependencies are considered 
during parsing; semantic dependencies are left 
for a later processing phase. The LEXSYS parser 
returns a complete set of all syntactically well- 
formed derivations. Semantic information can 
be recovered from derivation trees and then pro- 
cessed as desired. 
From a processing point of view, the XTAG and 
LEXSYS grammars are examples that show that 
the checking of dependencies involves a trade-off. 6 
On the one hand, a greater number of parses may 
be returned if the only dependencies checked are 
syntactic, since possible violations of semantic de- 
pendencies are ignored. On the other hand, as 
we have seen in this paper, there are potentially 
substantial benefits to parsing efficiency if all de- 
pendencies that the parser is checking can be lo- 
calized with the EDOL. It is tOO early to say how 
best to make the trade-off, but by comparing the 
way that the XTAG and LEXSYS grammars exploit 
the EDOL, we hope to have shed some light on 
the role that the EDOL can play with respect to 
parsing efficiency. 
6These are both grammars for English. Hence, 
whether the conclusions we draw apply to other lan- 
guages is outside the scope of the present work. 
5 Acknowledgements 
This work is supported by UK EPSR.C project 
GR/K97400 and by an EPSRC Advanced Fellow- 
ship to the first author. We would like to thank 
Roger Evans, Gerald Gazdar & K. Vijay-Shanker 
for helpful discussions. 
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