nils-herrmann/clean_scirepeval huggingface dataset:
Soft Constraints Mirror Hard Constraints: Voice and Person in English and Lummi

The same categorical phenomena which are attributed to hard grammatical constraints in some languages continue to show up as statistical preferences in other languages, motivating a grammatical model that can account for soft constraints. The effects of a hierarchy of person (1st, 2nd > 3rd) on grammar are categorical in some languages, most famously in languages with inverse systems, but also in languages with person restrictions on passivization. In Lummi, for example, the person of the subject argument cannot be lower than the person of a nonsubject argument. If this would happen in the active, passivization is obligatory; if it would happen in the passive, the active is obligatory (Jelinek and Demers 1983). These facts follow from the theory of harmonic alignment in OT: constraints favoring the harmonic association of prominent person (1st, 2nd) with prominent syntactic function (subject) are hypothesized to be present as subhierarchies of the grammars of all languages, but to vary in their effects across languages depending on their interactions with other constraints (Aissen 1999). There is a statistical reflection of these hierarchies in English. The same disharmonic person/argument associations which are avoided categorically in languages like Lummi by making passives either impossible or obligatory, are avoided in the SWITCHBOARD corpus of spoken English by either depressing or elevating the frequency of passives relative to actives. The English data can be grammatically analyzed within the stochastic OT framework (Boersma 1998, Boersma and Hayes 2001) in a way which provides a principled and unifying explanation for their relation to the crosslinguistic categorical person effects studied by Aissen (1999). 1 Categorical Effects of Person on Voice The effects of the person hierarchy (1) on grammar are categorical in some languages, most famously in languages with inverse systems, but also in languages with person restrictions on passivization. In Lummi (Straits Salish, British Columbia), for example, the person of the subject argument cannot be lower than the person of a nonsubject argument. If this would happen in the active, passivization is obligatory; if it would happen in the passive, the active is obligatory (Jelinek and Demers 1983, 1994).2 (1) Person hierarchy: 1st, 2nd 3rd (grammatical persons ‘local’ to speech act outrank others)
Interpreting and Extending Classical Agglomerative Clustering Algorithms using a Model-Based approach

We present two results which arise from a model-based approach to hierarchical agglomerative clustering. First, we show formally that the common heuristic agglomerative clustering algorithms -- single-link, complete-link, group-average, and Ward's method -- are each equivalent to a hierarchical model-based method. This interpretation gives a theoretical explanation of the empirical behavior of these algorithms, as well as a principled approach to resolving practical issues, such as number of clusters or the choice of method. Second, we show how a model-based approach can be used to extend these basic agglomerative algorithms. We introduce adjusted complete-link, Mahalanobis-link, and line-link as variants of the classical agglomerative methods, and demonstrate their utility.
The Recent Letter " Language, Trees and Zipping " [1] Suggests Using Standard

compression programs to solve a number of problems. Unfortunately, the ideas are well known, and the technique, tested on a standard problem, is at least a factor of three worse than a simple baseline. In particular, the ideas of this Letter are very well known in several fields of Computers Science, including Machine Learning and Statistical Natural Language Processing. This Letter is essentially showing several examples of text classification, a well studied area in both fields. Bayesian models of many sorts have already been applied to text classification, and Bayesian reasoning is equivalent to the MDL principal used in this Letter [2, page 463-464]. For a good overview, read, for instance, the Text Categorization chapter of Manning and Schütze[4] (a standard introductory textbook) where numerous Bayesian and other approaches are described. In addition, the zipping algorithm described here was invented by Rich Caruana in 1995, and described in a tutorial by Tom Mitchell in 1997 . , I give a broader description of the large body of related work. It is unfortunate that the authors did not try any of the standard algorithms used in Computer Science for problems of this type, or try their algorithm on any of the standard data sets. For comparison, I have implemented the zipping algorithm for a very similar, standard problem, 20 Newsgroups (determine the topic of a posting to one of 20 newsgroups.) I compared it to one of the simplest, easiest to implement algorithms used by Computer Scientists, the Naive Bayes model [4, page 238]. The zipping algorithm was 17 times slower and produced more than 3 times as many errors. It was only marginally simpler to implement, requiring 50 lines of perl script, instead of 70 lines. Omissions of this nature in a journal of the quality of Physical Review Letters are surprising and disappointing. In particular, although the concept of entropy originally was a Physics concept, it has been used and studied by Computer Scientists since the dawn of our field, and the information theoretic sense used here is not a strong link to physics. I suggest that authors writing letters essentially unrelated to physics may avoid embarrassing mistakes by submitting to journals that focus on the actual area of research, and that the editors of Physical Review Letters may avoid inappropriate publications by directing authors to those journals. Furthermore, editors and authors should be aware that computer scientists and other may feel insulted when those outside the field ignore its existence .
Agenda-Based Chart Parser for Arbitrary Probabilistic Context-Free Grammars

While O(n) methods for parsing probabilistic context-free grammars (PCFGs) are well known, a tabular parsing framework for arbitrary PCFGs which allows for botton-up, topdown, and other parsing strategies, has not yet been provided. This paper presents such an algorithm, and shows its correctness and advantages over prior work. The paper finishes by bringing out the connections between the algorithm and work on hypergraphs, which permits us to extend the presented Viterbi (best parse) algorithm to an inside (total probability) algorithm.
Parsing with Treebank Grammars: Empirical Bounds, Theoretical Models, and the Structure of the Penn Treebank

This paper presents empirical studies and closely corresponding theoretical models of the performance of a chart parser exhaustively parsing the Penn Treebank with the Treebank's own CFG grammar. We show how performance is dramatically affected by rule representation and tree transformations, but little by top-down vs. bottom-up strategies. We discuss grammatical saturation, including analysis of the strongly connected components of the phrasal nonterminals in the Treebank, and model how, as sentence length increases, the effective grammar rule size increases as regions of the grammar are unlocked, yielding super-cubic observed time behavior in some configurations.
Natural Language Grammar Induction Using a Constituent-Context Model

This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according to generative PCFG models. In contrast, we employ a simpler probabilistic model over trees based directly on constituent identity and linear context, and use an EM-like iterative procedure to induce structure. This method produces much higher quality analyses, giving the best published results on the ATIS dataset.
Kirrkirr: Software for Browsing and Visual Exploration of a Structured Warlpiri Dictionary

This paper presents an overview of the goals, architecture, and usability of Kirrkirr, a Java-based visualization tool for XML dictionaries, currently being used with a dictionary for Warlpiri, an Australian Aboriginal language. It discusses the underlying lexicon structure, and shows how a computer interface can effectively select from and display that content in various ways. The views of the dictionary include a graph view, which shows a network of semantically related words, and a formatted text view that can be customized via XSLT stylesheets. The paper argues that indigenous language dictionaries have normally been written for linguists, whereas the educational needs of other users have not been adequately met. It discusses the strengths of a computer dictionary interface in providing more help to native speaker users than a conventional dictionary, but argues that the possibilities for the visualization of dictionary information on computers have so far been insufficiently exploited. The paper concludes by briefly discussing observational and task-based testing of the dictionary with native speakers and learners.
Distributional phrase structure induction

Unsupervised grammar induction systems commonly judge potential constituents on the basis of their effects on the likelihood of the data. Linguistic justifications of constituency, on the other hand, rely on notions such as substitutability and varying external contexts. We describe two systems for distributional grammar induction which operate on such principles, using part-of-speech tags as the contextual features. The advantages and disadvantages of these systems are examined, including precision/recall trade-offs, error analysis, and extensibility.
Combining Heterogeneous Classifiers for Word Sense Disambiguation

This paper discusses ensembles of simple but heterogeneous classifiers for word-sense disambiguation, examining the Stanford-CS224N system entered in the SENSEVAL-2 English lexical sample task. First-order classifiers are combined by a second-order classifier, which variously uses majority voting, weighted voting, or a maximum entropy model. While individual first-order classifiers perform comparably to middle-scoring teams' systems, the combination achieves high performance. We discuss trade-offs and empirical performance. Finally, we present an analysis of the combination, examining how ensemble performance depends on error independence and task difficulty.
Parsing and Hypergraphs

While symbolic parsers can be viewed as deduction systems, this view is less natural for probabilistic parsers. We present a view of parsing as directed hypergraph analysis, which naturally covers both symbolic and probabilistic parsing. We illustrate the approach by showing how a dynamic extension of Dijkstra's algorithm can be used to construct a probabilistic chart parser with an O(n3) time bound for arbitrary PCFGs, while preserving as much of the flexibility of symbolic chart parsers as is allowed by the inherent ordering of probabilistic dependencies.
An O(n^3) Agenda-Based Chart Parser for Arbitrary Probabilistic Context-Free Grammars

While $O(n^3)$ methods for parsing probabilistic context-free grammars (PCFGs) are well known, a tabular parsing framework for arbitrary PCFGs which naturally allows top-down, bottom-up, and other strategies, corresponding to active chart parsing for CFGs, has not yet been provided. This paper presents such an algorithm, and shows its correctness and advantages over prior work. The paper finishes by bringing out the connections between the algorithm and work on hypergraphs, which permits us to extend the presented Viterbi (best parse) algorithm to an inside (total probability) algorithm.
Enriching the Knowledge Sources Used in a Maximum Entropy Part-of-Speech Tagger

This paper presents results for a maximum-entropy-based part of speech tagger, which achieves superior performance principally by enriching the information sources used for tagging. In particular, we get improved results by incorporating these features: (i) more extensive treatment of capitalization for unknown words; (ii) features for the disambiguation of the tense forms of verbs; (iii) features for disambiguating particles from prepositions and adverbs. The best resulting accuracy for the tagger on the Penn Treebank is 96.86% overall, and 86.91% on previously unseen words.
Bilingual Dictionaries for Australian Languages: User studies on the place of paper and electronic dictionaries

Dictionaries have long been seen as an essential contribution by linguists to work on endangered languages.
We report on preliminary investigations of actual dictionary usage and usability by 76 speakers,
semi-speakers and learners of Australian Aboriginal languages. The dictionaries include: electronic and
printed bilingual Warlpiri-English dictionaries, a printed trilingual Alawa-Kriol-English dictionary, and
a printed bilingual Warumungu-English dictionary. We examine competing demands for completeness of
coverage and ease of access, and focus on the prospects of electronic dictionaries for solving many traditional
problems, based in particular on observations on the usability of a prototype interface developed in
our project. The flexibility of computer interfaces can help accommodate different needs including those
of speakers with emerging literacy skills, but they are not useful in communities where computer access
is generally unavailable.
What's related? Generalizing approaches to related articles in medicine

We did formative evaluations of several variations to the computation of related articles for non-bibliographic resources in the medical domain.



A binary model and several variations of the vector space model were used to measure similarity between documents. Two corpora were studied, using a human expert as the gold standard.



Variations in term weights and stopword choices made little difference to performance. Performance was worse when documents were characterized by title words alone or by MeSH terms extracted from document references.



Further studies are needed to evaluate these methods in medical information retrieval systems.
Studies in Contemporary Phrase Structure Grammar: The lexical integrity of Japanese causatives

Grammatical theory has long wrestled with the fact that causative constructions exhibit properties of both single words and complex phrases. However, as Paul Kiparsky has observed, the distribution of such properties of causatives is not arbitrary: ‘construal’ phenomena such as honorification, anaphor and pronominal binding, and quantifier ‘floating’ typically behave as they would if causatives were syntactically complex, embedding constructions; whereas case marking, agreement and word order phenomena all point to the analysis of causatives as single lexical items. Although an analysis of causatives in terms of complex syntactic structures has frequently been adopted in an attempt to simplify the mapping to semantic structure, we believe that motivating syntactic structure based on perceived semantics is questionable because in general a syntax/semantics homomorphism cannot be maintained without vitiating syntactic theory (Miller 1991). Instead, we sketch a strictly lexical theory of Japanese causatives that deals with the evidence offered for a complex phrasal analysis. Such an analysis makes the phonology, morphology and syntax parallel, while a mismatch occurs with the semantics. The conclusions we will reach are given in (1):
Linguistics in an Age of Engineering

In the early days of engineering models of language, a popular intuition was that the easiest way to improve performance was to remove linguists. This was not an unreasonable, or even necessarily wrong intuition, and reflected the fixation by linguists of the day on linguistic structures to the exclusion of consideration of statistical dependencies between lexical or phrasal units or the non-categorical nature of real language use. But while the linguistics-blind approach showed promising initial beginnings, and the sheer brute-force nature of the approach led to the development and popularization of important statistical methods for dealing with sparse data, nevertheless, looking to the future, I'll argue that now the right way to improve engineering models is through the incorporation of more linguistics. But what kind of linguistics? I want to sketch how formal approaches to linguistics should reshape themselves from this brush with engineering: in a quantitative direction which is actually rather more compatible with much of the 'fuzzier' linguistic work in such topics as grammaticalization and sociolinguistics, though realized with more mathematical precision.
Publications received

Books listed below that are marked with a t have been selected for review in a future issue, and reviewers have been assigned to each. Authors and publishers who wish their publications to be considered for review in Computational Linguistics should send a copy to the book review editor, relevant books received will be listed, but not all can be reviewed. Technical reports (other than dissertations) will not be listed or reviewed. Authors should be aware that some publishers will not send books for review (even when instructed to do so); authors wishing to enquire as to whether their book has been received for review may contact the book review editor. Readers who wish to be considered as book reviewers for the journal should contact the book review editor, outlining their qualifications , by sending electronic mail to gh@cs. toronto.edu or by writing to the address above.
Argument Structure, Valence, and Binding

This paper develops within HPSG a model of grammar with two syntactic levels, valence lists and argument structure, at which sentences may have different representations: syntactically ergative and Western Austronesian languages are distinctive by allowing different prominence orderings between the valence lists and argument structure, while forms like passives and causatives have nested argument structure lists. While binding theory and related phenomena have traditionally been described in terms of surface grammatical relations or configurations, we demonstrate that binding theory is actually correctly described in terms of argument structure configurations. Such an approach generalizes nicely over accusative and ergative constructions, correctly predicts binding patterns with causative and passive verbs, and supports the lexicality-preserving account of passives and causatives advocated within HPSG.
Implementing Multi-Agent Systems: Languages, Frameworks, and Standards (Extended Abstract)*

As multi-agent systems research nears the end of its second decade, researchers have moved beyond stand-alone, one-off systems and have begun to create the software infrastructure for quickly creating new, highly interoperable systems. However, the desire for seamless interoperability ("open" systems) brings with it the push to standardize on agent communication languages and related agent service facilities. Although a host of theoretical and practical controversies surround the specification of such standards, some shared, guiding principles have emerged. Many researchers focus their work on the internal structures of agents (architecture), while others focus more on the activities and structures between agents (organization). The first principle is the realization that most principles can be recast at both the intraand inter(architectural and organizational) levels. The second principle is a drive toward the reuse of models and particular behaviors both conceptually, in reusable implementations, and in the creation of generic infrastructure components. The third principle revolves around how to structure individual or multi-agent knowledge and behaviors that includes techniques for composition, layering, and abstraction. The final guiding principle is the centrality of the interoperability question. After all, what would a multiagent system be unless there are in fact multiple agents interoperating with one another?! Methodologically, research in the area of agent frameworks and languages has been pursued in both a theory-driven and application-driven manner. Often there can be significant interaction between theory and practice, as in the development of BDI-based systems (Bratman 1987; Rao & Georgeff 1995). Although there are as yet no complete solutions, multi-agent system development methodologies will be important for the software engineer-
The segmentation problem in morphology learning

Recently there has been a large literature on various approaches to learning morphology, and the success and cognitive plausibility of different approaches (Rumelhart and McClelland (1986), MacWhinney and Leinbach (1991) arguing for connectionist models, Pinker and Prince (1988), Lachter and Bever (1988), Marcus et al. (1992) arguing against connectionist models, Ling and Marinov (1993), Ling (1994) using ID3/C4.5 decision trees, and Mooney and Califf (1995, 1996) using inductive logic programming/decision lists, among others). However - except for a couple of forays into German - this literature has been exclusively concerned with the learning of the English past tense. This has not worried some. Ling is happy to describe it as "a landmark task". But while the English past tense has some interesting features in its combination of regular rules with semi-productive strong verb patterns, it is in many other respects a very trivial morphological system - reflecting the generally vestigal nature of inflectional morphology within modern English.
Probabilistic Parsing using Left Corner Language Models

We introduce a novel parser based on a probabilistic version of a left-corner parser. The left-corner strategy is attractive because rule probabilities can be conditioned on both top-down goals and bottom-up derivations. We develop the underlying theory and explain how a grammar can be induced from analyzed data. We show that the left-corner approach provides an advantage over simple top-down probabilistic context-free grammars in parsing the Wall Street Journal using a grammar induced from the Penn Treebank. We also conclude that the Penn Treebank provides a fairly weak tes bed due to the flatness of its bracketings and to the obvious overgeneration and undergeneration of its induced grammar.
Dissociating functor-argument structure from surface phrase structure: the relationship of HPSG Orde

Recent work on order domains and linearization in HPSG, and also conceptually related work in categorial grammar, is argued to mirror the key ideas that motivated the separation between c-structure and f-structure in the earliest work in LFG (Bresnan 1982). This paper argues that: (i) to be descriptively adequate, all constraint-based frameworks do indeed need a dissociation between functor-argument structure and surface phrase structure, (ii) while linearization HPSG can technically be regarded as a one-level/one-stratum architecture, the complex attribute-value matrix representations proposed are better thought of as encoding multiplèvirtual levels', and (iii) once this is noted, there is a general equivalence between the analyses that can be proposed in linearization HPSG and LFG, although certain diierences are noted. grew out of a structuralist tradition that assumed a rather close relationship between units of functor-argument structure and units of surface phrase structure { indeed they hewed to this line closely, since they denied the need for transformational operations, which much of modern linguistics has used to produce dissoci-ations between the two (as in Chomsky (1957) and subsequent work). In contrast, Lexical Functional Grammar (LFG: Bresnan 1982) was designed to easily permit a much looser relationship between these two notions, and, recently, cases of marked deviation between these two levels have led researchers in HPSG to adopt an order domain or linearization frame-Special thanks to Ivan Sag for catching an analytical oversight in a previous version. I hope it is now somewhat clearer what I am trying to do.