32.1088, Review: Computational Linguistics; Pragmatics; Semantics: Bender, Lascarides (2019)

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Subject: 32.1088, Review: Computational Linguistics; Pragmatics; Semantics: Bender, Lascarides (2019)

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Date: Thu, 25 Mar 2021 17:01:58
From: Maria-Jose Arrufat-Marques [arrufatm at uji.es]
Subject: Linguistic Fundamentals for Natural Language Processing II

 
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Book announced at http://linguistlist.org/issues/30/30-4511.html

AUTHOR: Emily M. Bender
AUTHOR: Alex  Lascarides
TITLE: Linguistic Fundamentals for Natural Language Processing II
SUBTITLE: 100 Essentials from Semantics and Pragmatics
SERIES TITLE: Synthesis Lectures on Human Language Technologies edited by Graeme Hirst
PUBLISHER: Morgan & Claypool Publishers
YEAR: 2019

REVIEWER: Maria-Jose Arrufat-Marques, Universitat Jaume I

SUMMARY

This riveting volume is a compilation of 100 topics distributed in 14 chapters
that highlight the importance of linguistic knowledge, interactional context,
and the semantic and pragmatic mechanisms behind language understanding and
use, and their application for diverse natural language processing (NLP) tasks
involving written and spoken data. Each topic from 1 to 100 is addressed as
“#(number)”. For example,  “#0” and “#1” are the first ones and found in the
first paragraph below.

In Chapter 1, “Introduction”, #0 presents the main reasons why considering
semantics and pragmatics is important for NLP systems building. As the authors
state, the ultimate goal of NLP is to create systems able to transfer as much
information across different “domains, tasks, and speakers” (p. 1), which can
only be achieved once there is full comprehension of a language, including
semantics and pragmatics. #1 delves into this idea. Considering common sense
reasoning is essential in NLP, being knowledgeable about semantics can be
advantageous in devising systems to understand and generate language.

Chapter 2, “What is meaning?”, explores fundamental ideas related to the
meaning of natural language from a philosophical and formal semantics
perspective and the positive effects it may bring to include them to construct
NLP systems. #2 adopts a philosophical stance to describe the logic side of
language. #3 asserts that common reasoning, coherence, and world knowledge are
essential to comprehend natural languages. #4 tackles the different meaning
levels (i.e.: semantics, content, and implicature knowledge) required to
understand whole word meaning. #5 explains the differences and importance of
locutionary, illocutionary, and perlocutionary acts; and distinguishes them
from #4. #6 presents the importance of indirect speech acts and common ground
to correctly interpret anaphora. #7 highlights that speech acts are not only
properties of but also display relations among utterances. #8 and #9 show that
linguistic meaning not only refers to the actual meaning of the word, but also
the inclusion of emotions and social meaning. #10 discusses the ambiguous
nature of natural languages. #11 examines language processing differences
between NLP systems and humans. #12 and #13 illustrate that meaning in
face-to-face interaction emerges from both verbal and non-verbal behaviors and
the complex intricacy between them. #14 reports that meaning inference
differs, being more abstract if using a compositional semantics approach, and
more concrete if using coherence or cognitive cooperative techniques in
interaction.

Chapter 3, “Lexical Semantics: Overview”, tackles some main points in lexical
semantics. #15 discusses that understanding words from a formal grammar
perspective implies missing out much of their meaning. Words carry predictable
but also idiosyncratic features in their meaning and only from a more
comprehensive understanding of words will they be modelled optimally. #16
tackles three aspects inherent in individual words: word sense, semantic
roles, and connotations. #17 explores the applications of these three issues
to groups of words: multiword expressions (MWE). 

Chapter 4, “Lexical Semantic: Senses”, frames in depth the aforementioned
idiosyncratic, predicable, or productive nature of senses, as well as the
disadvantages and benefits it may bring to NLP systems. #18 explores the
multiple meanings words can have, which may differ depending on the usage
context and might transfer among languages. #19 and #20 tackle the various
types and relations of regular polysemy and constructional polysemy
respectively. #21 introduces homonymy, how it differs from polysemy, and the
benefits it brings to NLP. #22 and #23 relate to #19 as the former two discuss
a process to create new words and the latter linguistic and human issues that
can impede and resolve meaning problems in such new words. #24 presents
various ways that support the gradual meaning variation of words. #25
introduces vector space representations and #26 discusses it further in
relation to word meaning identification from a formal semantics viewpoint. #27
to #29 deal with metaphors and the matters that play a role in their creation,
meanings, and interpretations. #30 and #31 discuss the influence of transfer
and defeasible information in word senses.

Chapter 5, “Semantic Roles”, discusses how parts of a sentence (arguments)
relate to the linguistic object they refer to and to various linguistic
resources used to display such arguments. #32 explains that some arguments
exemplify the existence and variety of relationships among words or other
arguments. #33 explores the idea that syntax and word meaning will enhance the
identification of the different arguments in a sentence in relation to their
predicate. #34 identifies the granularity by which semantic roles can be
examined and thus classified. Some examples are given: FrameNet on one
extreme, PropBank and English Resource Grammar on the other, and VerbNet in
the middle. #35 provides some sentences where the foci are the verbs, by which
the authors explain that depending on the verb used, we expect one type of
specific complement (arguments) over others. #36 states that argument omission
does not imply meaning ambiguity. For example, subject omission presents no
problem in Japanese or Spanish, but it may be more problematic in English.
Regardless, the meaning comes across since other linguistic resources are
used. This issue is highlighted as essential to consider for NLP task
generation. 

Chapter 6 discusses “Collocations and Other Multiword Expressions” from a
semantics perspective, highlighting the necessity of using grammars and
parsers to consider their specific syntax and semantics features. #37
introduces MWEs, defined as co-existing groups of words having specific
meaning and form and allowing for some variation regarding their syntax,
semantic, pragmatic, or frequency of use. MWEs are considered single lexical
units because they can have multiple different meanings, which can vary over
time, and dynamic because new ones can be created. However, they pose some
difficulties for NLP specialists due to their particular forms and being
language specific. #38 focuses on collocations, a type of MWEs that depend
both on their form and meaning for a successful use and understanding. They
are difficult to learn -by humans and machines- due to their dialectal
variation, less frequent use, and the fact that substituting a word within a
collocation for a synonym will make an incorrect use and weird sense of the
whole unit. #39 provides examples such as “make a cake” or “heavy sleeper” to
explain that the sense of a collocation is clearer than the meaning of the
words conforming it on their own. #40 discusses that collocation frequency and
strength do not go hand in hand and that accessing and using large corpora and
metrics will make the task of building up NLP systems more accurate and
effective. #41 comments on the fact that MWEs are ambiguous and that sense
extension can stem from a polysemic, homonymic, and metaphorical relationship
between the senses. #42 tackles the different ways to generate MWEs. However,
the resulting MWEs may be just one word; and this is a difficulty for building
NLP systems, as they need to be trained to recognize all lexical particles
that fulfill the same semantic sense. #43 discusses the phenomena of
grammaticalization and idiomatization as two possible ways for a language to
acquire new MWEs. #44 discusses the syntactic flexibility of MWEs, meaning
that some do not allow any change -thus being fixed expressions- and others
accept some word order change, i.e., idiomatically combining expressions. The
authors express the need to develop parsers that identify both types of
expressions in a precise and accurate manner. #45 tackles the phenomenon of
compositionality in MWEs, a phenomenon by which certain types of MWEs will
allow some variation(s) in their form that will not affect their meaning, and
which happen in many languages. #46 depicts the difficulty that may be brought
by trying to embody the meaning of the idiomatic expression with the meaning
of the parts conforming it. Thus, this needs to be included in grammars, where
the authors state the need to address this issue by for example flagging the
specific meanings of certain words when used in idiomatic expressions, so that
the grammar can identify each use accurately. 

Chapter 7, “Compositional Semantics”, focuses on meaning representation
composition from a formal semantic approach, being truth and reference key
aspects related to compositional semantics, to ultimately make predictions
about logical relationships. #47 introduces what compositional semantics is.
It studies the representation of the predicate-argument structure by means of
syntactic analyses. Attention is given to other important related issues,
including wedge elimination, entailment, and validity. #48 presents different
options to represent compositional semantics, such as semantic typing,
grounded language acquisition, and broad coverage parsing. #49 discusses that
expression of comparative relations is language dependent considering the
following three essential elements may vary among languages: “the gradable
property, the entity bearing the property, and a standard of comparison” (p.
77). #50 explains how subtle meaning differences may arise from interpreting
coordinated sentences and states that systems used for NLU may need to be
trained and prepared to discern such different semantic interpretations. #51
to #53 tackle quantifiers and how they semantically influence and relate to
other components in a sentence or text from a set theory perspective, which is
the base of formal semantics. In contrast to #53, #54 discusses that the
meaning of other scopal operators (e.g., negation) can indeed be sorted out by
closely looking at syntax. #55 states that the NLP application selected will
decide how to best represent scopal operators, this not being critical for
applications such as information retrieval, but it is essential for
classification tasks. #56 reports on the interplay between word senses and
compositional semantics as seen in syntactic analyses since the former are
structured and semantically complex, including nouns and quantifiers. #57
discusses different ways to infer semantic equivalence, including
distributional models of words, vector averaging, composition, or
grammar-driven approaches.

The scope of Chapter 8, “Compositional Semantics Beyond Predicate-Argument
Structure”, is summarized in #58: compositional semantics not only explores
morphology and syntax, but also other language elements including tense,
aspect, evidentials, presuppositions, and politeness. #59 focuses on the
different ways that arguments can be identified, e.g.: word order, case
marking, or agreement markers, as dictated by language. #60 discusses tense
based on Reichenbach’s (1947) interpretation, in contrast to Prior’s (1957).
Reichenbach proposes three key elements determining the use of a (past) tense:
the speech time, event time, and reference time whose element it refers to
anaphorically is specified by the situational context. #61 comments on aspect,
as it portrays the internal temporal properties on a given event--situational
aspect--and how it is perceived -viewpoint aspect. These two systems interact,
the former being lexical and compositional in nature; and the second referring
to the grammatical resources a language offers to express a temporal
perspective of a given context. #62 tackles evidentials, which encompass the
origin of the information a person refers to and how certain said person is
about said information. Depending on the language, evidentiality may be
grammaticalized or not. #63 and #64 discuss politeness, which can be expressed
via grammaticalized forms, and other words, such as ‘please’ or the use of
mitigators (‘could’ instead of ‘can’) to show social distance and save
speaker’s face. #65 focuses on politeness markers to solve reference problems,
explaining it with the Japanese honorific system.

Chapter 9, “Beyond Sentences”, looks into contextual elements essential to
resolve ambiguity difficulties. #66 and #67, from a coherence-based model
perspective, assert that to comprehend discursive meaning an update function
is needed to understand the information conveyed in a coherent and structured
manner and the context where this occurs. #68 illustrates that word meaning
understanding will lead to understanding discourse and vice versa: word
processing enhances discourse comprehension and a structured discourse
facilitates word ambiguity solving. #69 explains discourse understanding from
a dynamic semantics perspective. #70 discusses the pros and cons of using game
theory to understand discourse and generate dialogues.

Chapter 10, “Reference Solution”, underscores the essential role of linguistic
context to identify referents in discourse understanding and its NLP
applications. #71 illustrates the importance of reference identification and
application in NLP tasks to process discourse. #72 discusses the different
types of referents. #73 describes various grammatical features affecting
referents and their antecedents. #74 reports on the unambiguous, logical
nature of the discourse segment where the antecedent can be found. #75
explains the effect of modals, negations, and conditionals. #76 discusses the
importance of discourse structure and discourse coherence particularly.

Chapter 11, “Presupposition”, concentrates on the effect of different
phenomena when processing presuppositions. #77 differentiates entailments from
presuppositions, both being sentence properties. #78 exemplifies the different
types of presupposition triggers, i.e., the words or expressions prefacing
presuppositions, which vary among languages. #79 illustrates the complexity of
presupposition depending on the linguistic features used to express it. #80
discusses that and exemplifies how presuppositions will be accommodated only
when there is no discourse antecedent. #81, similar to #76, shows discourse
coherence is also very relevant in understanding presupposition.

Chapter 12, “Information Status and Information Structure”, explains these
linguistic phenomena and describes different factors influencing them. #82
introduces information status via the components of an implication hierarchy
to demonstrate the linguistic connections between words and their referents to
speakers’ shared knowledge. #83 exemplifies the different morphological and
syntactic options to demonstrate information status, which vary across
languages. #84 introduces information structure, differing from information
status, as it shows that utterances can be new or given depending on the
context, marked by prosody, and having meaning and marking components. #85
discusses the four complex concepts by which the meaning of information
structure can be expressed: topic, focus, background, and contrast. #86
illustrates different morphological (prosody, lexis) and syntactical means to
express information structure marking across languages. #87 describes that
information structure marking is achieved most reliably by considering both
prosodic stress and tune together. #88 argues that both information structure
and truth conditions interplay to resolve semantic ambiguity.

Chapter 13, “Implicature and Dialogue”, observes contextual devises being
fundamental to resolve ambiguity issues from both semantics and pragmatics
perspectives. #89 defines and exemplifies implicatures, as implied meaning
conveyed by the speaker that surpasses the linguistic meaning of the
utterance. #90 discusses Grice’s (1975) implicatures (conversational and
conventional) and the four conversational maxims from which the former
implicatures come in order to understand implicatures and language users’
inferring mechanisms in communication. #91 asserts that cognitive reasoning is
not always needed to understand implicatures, and introduces the rationale
behind coherence-based theories to support that statement. #92 describes that
comprehending and creating semantic meaning should not be done following the
same logic pathways, meaning less time should be needed to do the latter and
more to achieve the former. #93 tackles the “safety” of using implicatures in
conversation; considering the aim of the speaker and the interpretation of the
hearer, the consequences can be (un)safe. #94 exemplifies how utterances and
implicatures can be rejected or agreed upon explicitly or implicitly. #95
exemplifies how silence can also be meaningfully used as an implicature tool,
mainly when speakers do not think alike. #96 emphasizes the importance of
prosody to influence on speaker’s stance, and describes why this should be
considered in NLP systems building. 

Chapter 14, “Resources”, encompasses a series of resources to analyze semantic
representations from smaller to bigger units. #97 exemplifies a wide range of
tools to identify and categorize lexical semantic meaning useful to apply in
different NLP tasks. #98 focuses on semantic meaning at the sentence level,
providing examples of sembanks, a compilation of texts that include semantic
annotations. #99 illustrates a series of sembank-trained and grammar-based
parsers that incorporate annotations to represent meaning. #100 describes a
series of different corpora that also include annotations of discourse
meaning. A summary of the main goals the authors aim to obtain with this
volume is included at the end of this chapter. 

EVALUATION

This book is an excellent, well-documented compilation of integral linguistic,
semantic, and contextual matters that affect language use and understanding
and their application to NLP. These are the main objectives the authors aim to
achieve and that have been discussed thoroughly throughout this volume. A
positive trait of this volume is the title of each of the 100 topics, which is
a summary of the content explored in each topic. This was a very helpful first
step to understanding the topics before diving into each of them.
Additionally, the organization of all 100 topics in 14 chapters is coherent,
and such organization makes the comprehension of all these issues clear and
more schematized. Some of the subjects discussed may be difficult to
understand if the reader does not have any previous knowledge of computational
linguistics, formal logic, NLP or machine learning. This is the one drawback I
would point out from this volume. Nevertheless, the examples and explanations
compensate for that shortcoming. Another issue I found is that it refers to
semantics and pragmatics but I have felt that more prominence is given to
semantics and formal semantics to explain and describe even pragmatic aspects
of the language. Coming from an applied pragmatics training, I was expecting a
more social or applied pragmatics approach to some of the issues discussed.
Nevertheless, exploring familiar linguistic and contextual aspects from
another perspective has been informative and enlightening. A very positive
aspect I would like to highlight is all the lines for further research that
the authors identify all throughout their volume. This makes this piece of
work of highly research value. 

This book may be useful for a varied audience, ranging from PhD students to
more experienced scholars in different subfields of linguistics to engineers
working on NLP tasks and NLU research who might find enriching the
consideration of the linguistic nature of such processes. In sum, this volume
is an important example of interdisciplinary research and work that puts
forward the essential role of different linguistic forms, their meaning, and
the importance of context for language usage and understanding and the wide
range of applications in NLP. 

REFERENCES

Prior, Arthur. 1957. Time and modality. Oxford University Press. 

Reichenbach, Hans. 1947. Elements of symbolic logic. Macmillan.


ABOUT THE REVIEWER

María-José Arrufat-Marqués holds a PhD in Applied Linguistics from Universitat
Jaume I (Spain). As a Fulbright scholar, she earned a MA in Applied Second
Language Acquisition from Carnegie Mellon University (USA). María-José’s
research interests include: second language acquisition, interlanguage
pragmatics, pragmatic development, formulaic language, technology-enhanced
language learning and teaching, and language attitudes.





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