acl acl2010 acl2010-207 knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Weiwei Sun
Abstract: One deficiency of current shallow parsing based Semantic Role Labeling (SRL) methods is that syntactic chunks are too small to effectively group words. To partially resolve this problem, we propose semantics-driven shallow parsing, which takes into account both syntactic structures and predicate-argument structures. We also introduce several new “path” features to improve shallow parsing based SRL method. Experiments indicate that our new method obtains a significant improvement over the best reported Chinese SRL result.
Reference: text
sentIndex sentText sentNum sentScore
1 uni i Abstract One deficiency of current shallow parsing based Semantic Role Labeling (SRL) methods is that syntactic chunks are too small to effectively group words. [sent-2, score-0.864]
2 To partially resolve this problem, we propose semantics-driven shallow parsing, which takes into account both syntactic structures and predicate-argument structures. [sent-3, score-0.455]
3 We also introduce several new “path” features to improve shallow parsing based SRL method. [sent-4, score-0.427]
4 1 Introduction In the last few years, there has been an increasing interest in Semantic Role Labeling (SRL) on several languages, which consists of recognizing arguments involved by predicates of a given sentence and labeling their semantic types. [sent-6, score-0.233]
5 Both full parsing based and shallow parsing based SRL methods have been discussed for English and Chinese. [sent-7, score-0.493]
6 In Chinese SRL, shallow parsing based methods that cast SRL as the classification of syntactic chunks into semantic labels has gained promising results. [sent-8, score-0.939]
7 , 2009) outperforms the best published performance of full parsing based SRL systems. [sent-10, score-0.137]
8 Because of the semantic information it contains, we call it semantics-driven shallow parsing. [sent-13, score-0.37]
9 The key idea is to make basic chunks as large as possible but not overlap with arguments. [sent-14, score-0.374]
10 Additionally, we introduce several new “path” features to express more structural information, which is important for SRL. [sent-15, score-0.048]
11 With semantics-driven shallow parsing, our SRL system achieves 76. [sent-17, score-0.265]
12 2 Related Work CPB is a project to add predicate-argument relations to the syntactic trees of the Chinese TreeBank (CTB). [sent-24, score-0.098]
13 Similar to English PropBank, the arguments of a predicate are labeled with a contiguous sequence of integers, in the form of AN (N is a natural number); the adjuncts are annotated as such with the label AM followed by a secondary tag that represents the semantic classification of the adjunct. [sent-25, score-0.281]
14 To partially resolve this problem, we propose a new shallow parsing. [sent-28, score-0.33]
15 The new chunk definition takes into account both syntactic structure and predicate-argument structures A0, meaning that it is the proto-Agent of “提供”. [sent-29, score-0.612]
16 (2009) explore the Chinese SRL problem on the basis of shallow syntactic information at the level of phrase chunks. [sent-31, score-0.434]
17 They present a semantic chunking method to resolve SRL on basis of shallow parsing. [sent-32, score-0.664]
18 Their method casts SRL as the classification of syntactic chunks with IOB2 representation for semantic roles (i. [sent-33, score-0.56]
19 semantic account 103 UppsalaP,r Sowce ed ein ,g 1s1 o-f16 th Jeu AlyC 2L0 210 1. [sent-35, score-0.105]
20 Two labeling strategies are presented: 1) directly tagging semantic chunks in one-stage, and 2) identifying argument boundaries as a chunking task and labeling their semantic types as a classification task. [sent-40, score-1.026]
21 On the basis of syntactic chunks, they define semantic chunks which do not overlap nor embed using IOB2 representation. [sent-41, score-0.613]
22 Syntactic chunks outside a chunk receive the tag O (Outside). [sent-42, score-0.784]
23 For syntactic chunks forming a chunk of type A *, the first chunk receives the B-A* tag (Begin), and the remaining ones receive the tag I-A * (Inside). [sent-43, score-1.335]
24 The definition of syntactic and semantic chunks is illustrated Figure 1. [sent-47, score-0.595]
25 For example, “保险公司/the insurance company”, consisting of two nouns, is a noun phrase; in the syntactic chunking stage, its two components “保 险” and “公 司” should be labeled as B-NP and I-NP. [sent-48, score-0.355]
26 Because this phrase is the Agent of the predicate “提 供/provide”, it takes a semantic chunk label B-A0. [sent-49, score-0.63]
27 In the semantic chunking stage, this phrase should be labeled as B-A0. [sent-50, score-0.354]
28 Their experiments on CPB indicate that according to current state-of-the-art of Chinese parsing, SRL systems on basis of full parsing do not perform better than systems based on shallow parsing. [sent-51, score-0.415]
29 They report the best SRL performance with gold segmentation and POS tagging as inputs. [sent-52, score-0.046]
30 In English SRL, previous work shows that full parsing, both constituency parsing and dependency parsing, is necessary. [sent-54, score-0.114]
31 Ding and Chang (2009) discuss semantic chunking methods without any parsing information. [sent-55, score-0.433]
32 , 2009), their method formulates SRL as the classification of words with semantic chunks. [sent-57, score-0.127]
33 Comparison of experimental results in their work shows that parsing is necessary for Chinese SRL, and the semantic chunking methods on the basis of shallow parsing outperform the ones without any parsing. [sent-58, score-0.848]
34 Joint learning of syntactic and semantic structures is another hot topic in dependency parsing research. [sent-59, score-0.341]
35 The CoNLL 2008/2009 shared tasks propose a unified dependency-based formalism to model both syntactic dependencies and semantic roles for multiple languages. [sent-63, score-0.241]
36 Several joint parsing models are presented in the shared tasks. [sent-64, score-0.152]
37 In this paper, we hope to find better syntactic representation for semantic role labeling. [sent-66, score-0.236]
38 1 Motivation There are two main jobs of semantic chunking: 1) grouping words as argument candidate and 2) classifying semantic types of possible arguments. [sent-68, score-0.3]
39 Previously proposed shallow parsing only considers syntactic information and basic chunks are usu- ally too small to effectively group words. [sent-69, score-0.812]
40 the argument “为 三 峡 程/for the Sanxia Project” consists of three chunks, each of which only consists of one word. [sent-73, score-0.063]
41 To rightly recognize this A2, Semantic chunker should rightly predict three chunk labels. [sent-74, score-0.468]
42 Small chunks also make the important “path” feature sparse, since there are more chunks between a target chunk and the predicate in focus. [sent-75, score-1.159]
43 In this section, we introduce a new chunk definition to improve shallow parsing based SRL, which takes both syntactic and predicateargument structures into account. [sent-76, score-1.018]
44 The key idea is to make syntactic chunks as large as possible for semantic chunking. [sent-77, score-0.538]
45 , wn, let c[i : j] denote a constituent that is made up of words between wi and wj (including wi and wj); let pv = {c[i : j] |c[i : j] is an argument of v} 104 denote one predicate-argument structure where v is the predicate in focus. [sent-83, score-0.235]
46 Given a syntactic tree Ts = {c[i : j] |c[i : j] is a constituent of s}, and Tits a=ll argument s[itru :c jtu]r iess Ps = {pv | v oisf a }ve,r abnadl predicate uinm s}, stthruercet irse one a=nd { only one cvherubnakl sperte dCi = {c[i : j] } hse. [sent-84, score-0.32]
47 ∀c[i : j] ∈ C, ∀c[iv : jv] ∈ ∪Ps, j < iv or i∀ jv or ∈iv ≤ i∀ ≤ j ≤ jv; > 3. [sent-88, score-0.106]
48 The first condition guarantees that every chunk is a constituent. [sent-92, score-0.475]
49 The second condition means that chunks do not overlap with arguments, and further guarantees that semantic chunking can recover all arguments with the last condition. [sent-93, score-0.817]
50 The third condition makes new chunks as big as possible. [sent-94, score-0.4]
51 Figure t2a i ns an example ptoo nilelnust-s trate our new chunk definition. [sent-96, score-0.409]
52 For example, “中 国/Chinese 税 务/tax 部 分/department” is a constituent of current sentence, and is also an argument of “规定/stipulate”. [sent-97, score-0.098]
53 If we take it as a chunk, it does not conflict with any other arguments, so it is a reasonable syntactic chunk. [sent-98, score-0.098]
54 For the phrase “欠缴/owing 税款/tax payment”, though it does not overlap with the first, third and fourth propositions, it is bigger than the argument “税款” (conflicting with condition 2) while labeling the predicate “欠缴”, so it has to be separated into two chunks. [sent-99, score-0.35]
55 Note that the third condition also guarantees the constituents in C does not overlap with aeantcehe sot thheer soinnsceti ueaenchts one Cis d as large as possible. [sent-100, score-0.149]
56 So we can still formulate our new shallow parsing as an “IOB” sequence labeling problem. [sent-101, score-0.491]
57 The column CHUNK 1 illustrates this kind of chunk type definition. [sent-105, score-0.461]
58 Inspired by (Klein and Manning, 2003), we split one phrase type into several subsymbols, which contain category information of current constituent’s parent. [sent-107, score-0.061]
59 This strategy severely increases the number of chunk types and make it hard to train chunking models. [sent-109, score-0.602]
60 At both ends, the chain is terminated with the POS tags of the predicate and the headword of the token. [sent-117, score-0.078]
61 For example, the path feature of “保 险 公 司” in Figure 1 is “公司-ADVP-PP-NP-NP-VV”. [sent-118, score-0.149]
62 To better capture structural information, we introduce several new “path” features. [sent-120, score-0.048]
63 They include: • NP |PP|VP path: only syntactic chunks tNhaPt| taPk|VesP tag NP, PP or VP are kept. [sent-121, score-0.472]
64 105 When labeling the predicate “出 境/leave the country” in Figure 2, this feature of “中 国 税 务 部 门/Chinese tax departments” is NP+NP+NP+NP+VP. [sent-122, score-0.215]
65 O2POS path: if a word occupies a chunk lOab2ePl O, use iitfs P wOoSr i onc tuhpei path fuenakture. [sent-124, score-0.514]
66 The data is divided into three parts: files from chtb 081 to chtb 899 are used as training set; files from chtb 041 to chtb 080 as development set; files from chtb 001 to chtb 040, and chtb 900 to chtb 93 1 as test set. [sent-134, score-1.602]
67 Both syntactic chunkers and semantic chunkers are trained and evaluated by us- ing the same data set. [sent-135, score-0.297]
68 By using CPB and CTB, we can extract gold standard semantics-driven shallow chunks according to our definition. [sent-136, score-0.623]
69 We use this kind of gold chunks automatically generated from training data to train syntactic chunkers. [sent-137, score-0.48]
70 For both syntactic and semantic chunking, we used conditional random field model. [sent-138, score-0.203]
71 Crfsgd provides a feature template that defines a set of strong word and POS features to do syntactic chunking. [sent-140, score-0.121]
72 We use this feature template to resolve shallow parsing. [sent-141, score-0.332]
73 For semantic chunking, we implement a similar onestage shallow parsing based SRL system described in (Sun et al. [sent-142, score-0.484]
74 First, our system uses Start/End method to represent semantic chunks (Kudo and Matsumoto, 2001). [sent-146, score-0.44]
75 2 Syntactic Chunking Performance Table 1 shows the performance of shallow syntactic parsing. [sent-166, score-0.386]
76 , 2006 is the chunking performance evaluated on syntactic chunk definition proposed in (Chen et al. [sent-168, score-0.78]
77 The second and third blocks present the chunking performance with new semantics-driven shallow parsing. [sent-170, score-0.55]
78 The second block shows the overall performance when the first kind of chunks type is used, while the last block shows the performance when the more complex chunk type definition is used. [sent-171, score-0.968]
79 For the semantic-driven parsing experiments, we add the path from current word to the first verb before or after as two new features. [sent-172, score-0.261]
80 Because the two new chunk definitions use the same chunk boundaries, the fourth and sixth lines are comparable. [sent-175, score-0.797]
81 There is a clear decrease between the traditional shallow parsing (Chen et al. [sent-176, score-0.379]
82 We think one main reason is that syntactic chunks in our new definition are larger than the traditional ones. [sent-178, score-0.511]
83 An interesting phenomenon is that though the second kind of chunk type definition increases the complexity of the parsing job, it achieves better bracketing performance. [sent-179, score-0.652]
84 These two systems are both evaluated by using syntactic chunking defined in (Chen et al. [sent-188, score-0.312]
85 From the first block we can see that our semantic chunking system reaches the state-of-the-art. [sent-190, score-0.352]
86 The second and third blocks in Table 2 present the performance with 1http : / / le on . [sent-191, score-0.05]
87 o rg/pro j e ct s / s gd 106 new shallow parsing. [sent-193, score-0.286]
88 Line SRL (C1) and SRL (C2) show the overall performances with the first and second chunk definition. [sent-194, score-0.388]
89 We can see that new “path” features are useful for semantic chunking. [sent-196, score-0.126]
90 , 2006)], SRL [C1] and SRL [C2] respetively denote the SRL systems based on shallow parsing defined in (Chen et al. [sent-210, score-0.379]
91 5 Conclusion In this paper we propose a new syntactic shallow parsing for Chinese SRL. [sent-212, score-0.498]
92 The new chunk definition contains both syntactic structure and predicate-argument structure information. [sent-213, score-0.564]
93 To improve SRL, we also introduce several new “path” features. [sent-214, score-0.048]
94 Experimental results show that our new chunk definition is more suitable for Chinese SRL. [sent-215, score-0.466]
95 It is still an open question what kinds of syntactic information is most important for Chinese SRL. [sent-216, score-0.098]
96 We suggest that our attempt at semantics-driven shallow parsing is a possible way to better exploit this problem. [sent-217, score-0.379]
97 Improving Chinese semantic role classification with hierarchical feature selection strategy. [sent-227, score-0.183]
98 Fast semantic role labeling for Chinese based on semantic chunking. [sent-232, score-0.334]
99 The CoNLL-2009 shared task: Syntactic and semantic dependencies in multiple languages. [sent-238, score-0.143]
100 The conll 2008 shared task on joint parsing of syntactic and semantic dependencies. [sent-268, score-0.392]
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