Building a Large Annotated Corpus of English: The Penn Treebank

Marcus, Mitchell P.; Marcinkiewicz, Mary Ann; Santorini, Beatrice

doi:10.21236/ada273556

Cited by 3,855 publications

(3,406 citation statements)

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“…The parser used was Roark's (2001) incremental top-down parser. This is a probabilistic parser trained on the Penn Treebank (Marcus, Santorini, & Marcinkiewicz, 1993), a corpus of English text manually annotated with phrase structure trees. Only the Wall Street Journal section of the Penn Treebank was used for training.…”

Section: Methodsmentioning

confidence: 99%

Data from eye-tracking corpora as evidence for theories of syntactic processing complexity

2008

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We evaluate the predictions of two theories of syntactic processing complexity, dependency locality theory (DLT) and surprisal, against the Dundee corpus, which contains the eye-tracking record of 10 participants reading 51,000 words of newspaper text. Our results show that DLT integration cost is not a significant predictor of reading times for arbitrary words in the corpus. However, DLT successfully predicts reading times for nouns and verbs. We also find evidence for integration cost effects at auxiliaries, not predicted by DLT. For surprisal, we demonstrate that an unlexicalized formulation of surprisal can predict reading times for arbitrary words in the corpus. Comparing DLT integration cost and surprisal, we find that the two measures are uncorrelated, which suggests that a complete theory will need to incorporate both aspects of processing complexity. We conclude that eye-tracking corpora, which provide reading time data for naturally occurring, contextualized sentences, can complement experimental evidence as a basis for theories of processing complexity.

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Section: Methodsmentioning

confidence: 99%

Data from eye-tracking corpora as evidence for theories of syntactic processing complexity

2008

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“…Log-transformed lexical frequency counts were generated from the SUBTLEXus corpus (Brysbaert and New, 2009). Each sentence was parsed using Roark's (Roark, 2001;Roark et al, 2009) incremental top-down PCFG parser trained on the Wall Street Journal corpus of the Penn Treebank (Marcus et al, 1993) to generate syntactic surprisal values for each word.…”

Section: Language Statisticsmentioning

confidence: 99%

Language structure in the brain: A fixation-related fMRI study of syntactic surprisal in reading

et al. 2016

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How is syntactic analysis implemented by the human brain during language comprehension? The current study combined methods from computational linguistics, eyetracking, and fMRI to address this question. Subjects read passages of text presented as paragraphs while their eye movements were recorded in an MRI scanner. We parsed the text using a probabilistic context-free grammar to isolate syntactic difficulty. Syntactic difficulty was quantified as syntactic surprisal, which is related to the expectedness of a given word's syntactic category given its preceding context. We compared words with high and low syntactic surprisal values that were equated for length, frequency, and lexical surprisal, and used fixation-related (FIRE) fMRI to measure neural activity associated with syntactic surprisal for each fixated word. We observed greater neural activity for high than low syntactic surprisal in two predicted cortical regions previously identified with syntax: left inferior frontal gyrus (IFG) and less robustly, left anterior superior temporal lobe (ATL). These results support the hypothesis that left IFG and ATL play a central role in syntactic analysis during language comprehension. More generally, the results suggest a broader cortical network associated with syntactic prediction that includes increased activity in bilateral IFG and insula, as well as fusiform and right lingual gyri.© 2016 Elsevier Inc. All rights reserved. Keywords:Language Syntax Surprisal Reading Eye movements fMRI IntroductionA complete theory of the human brain must include a description of the neural networks responsible for language processing. Comprehension of connected sentences requires the ability to retrieve words from the lexicon and relate those words to each other, as the input is encountered in real time. The system for creating these groupings is known as syntax, and is generally thought of as a set of computations specifying syntactic categories such as noun and verb, and stating how those categories combine into increasingly larger constituents such as noun phrases, verb phrases, and clauses. The constituent structure of a sentence is the frame on which interpretations are built; the same words will have radically different meanings depending on that structure (e.g., the dog bit the man vs. the man bit the dog). Thus, the human ability to understand language is based both on lexical knowledge and syntactic computations.In this study, we focused on understanding how the human brain implements the syntactic component of the human language faculty. Specifically, we were interested in the nature of the cortical systems that compute syntactic representations during online language comprehension. Three regions have traditionally been identified as candidates for syntactic processing (Fedorenko et al., 2012;Friederici and Kotz, 2003;Grodzinsky and Friederici, 2006;Kaan and Swaab, 2002). Historically, Broca's area or left inferior frontal gyrus (IFG) has been most associated with syntax (Ben-Shachar et al., 2003;Ben-Shachar et al., 2004;...

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“…These 1127 tokens were then combined with 1263 tokens from the Switchboard Corpus (Godfrey et al 1992), and 404 written tokens from the Treebank Wall-Street Journal (Marcus et al 1993). …”

Section: The Data From Nz and Us Englishmentioning

confidence: 99%

Gradient grammar: An effect of animacy on the syntax of give in New Zealand and American English

Bresnan

Hay

2008

Lingua

219

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Bresnan et al. (2007) show that a statistical model can predict United States (US) English speakers' syntactic choices with 'give'-type verbs extremely accurately. They argue that these results are consistent with probabilistic models of grammar, which assume that grammar is quantitive, and learned from exposure to other speakers. Such a model would also predict syntactic differences across time and space which are reflected not only in the use of clear dialectal features or clear-cut changes in progress, but also in subtle factors such as the relative importance of conditioning factors, and changes over time in speakers' preferences between equally well-formed variants. This paper investigates these predictions by comparing the grammar of phrases involving 'give' in New Zealand (NZ) and US English. We find that the grammar developed by Bresnan et al. for US English generalizes remarkably well to NZ English. NZ English is, however, subtly different, in that NZ English speakers appear to be more sensitive to the role of animacy. Further, we investigate changes over time in NZ English and find that the overall behavior of 'give' phrases has subtly shifted. We argue that these subtle differences in space and time provide support for the gradient nature of grammar, and are consistent with usage-based, probabilistic syntactic models.

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Building a Large Annotated Corpus of English: The Penn Treebank

Abstract: 13Cont,act The Ling11ist.i~ Da.ta Consortil~m. 441 l17illianls Ilall. I~'nivc.r>it!-ol'Prtlr~syl~.ania. I'hilatlelpllia, PA 19104-6305 or send email to ltlc~Ci~~~~ra.gi.ci~.r~l~enn.ed for ulore if o r r~~a t i o n .

Cited by 3,855 publications

References 10 publications

Data from eye-tracking corpora as evidence for theories of syntactic processing complexity

Data from eye-tracking corpora as evidence for theories of syntactic processing complexity

Language structure in the brain: A fixation-related fMRI study of syntactic surprisal in reading

Gradient grammar: An effect of animacy on the syntax of give in New Zealand and American English

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Building a Large Annotated Corpus of English: The Penn Treebank

Abstract: 13Cont,act The Ling11ist.i~ Da.ta Consortil~m. 441 l17illianls Ilall. I~'nivc.r>it!-ol'Prtlr~syl~.ania. I'hilatlelpllia, PA 19104-6305 or send email to ltlc~Ci~~~~ra.gi.ci~.r~l~enn.ed~~ for ulore i~~f o r r~~a t i o n .

Cited by 3,855 publications

References 10 publications

Data from eye-tracking corpora as evidence for theories of syntactic processing complexity

Data from eye-tracking corpora as evidence for theories of syntactic processing complexity

Language structure in the brain: A fixation-related fMRI study of syntactic surprisal in reading

Gradient grammar: An effect of animacy on the syntax of give in New Zealand and American English

Contact Info

Product

Resources

About

Abstract: 13Cont,act The Ling11ist.i~ Da.ta Consortil~m. 441 l17illianls Ilall. I~'nivc.r>it!-ol'Prtlr~syl~.ania. I'hilatlelpllia, PA 19104-6305 or send email to ltlc~Ci~~~~ra.gi.ci~.r~l~enn.ed for ulore if o r r~~a t i o n .