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`Page 1 of 12
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`GOOGLE EXHIBIT 1031
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`late 1960s, the second from the late 60s to the late 70s and the third to the late 80s, with
`the fourth phase to the end of the century. The first phase was driven by MT, the second
`flavoured by AI, the third grammatico-logical, while the fourth phase has focused on lexical
`and corpus data. This last phase illustrates the cyclic character of work in the field, since
`it has returned to a major concern of the first period, namely building the powerful and
`comprehensive dictionaries that serious NLP applications like MT need, and has revived
`early proposals for extracting linguistic information from large natural corpora. At the same
`time, it also illustrates the extent to which real progress has been madein the field in such
`key areas as computational grammarand parsing.
`
`2 Phase 1: late 1940s to late 1960s
`
`§o¨©cª¬«­ ®¯ °±{© ²ª^°cª³!´'µ¶+·j¸ ´'¹º© ²&ª^§o¨©cª®¯ °(©c´¬© ²&ª§o¨©cª¼»-¯ °(¨ µŒ¶ © ²&ª½© ²¾o¸M¶©c´¿© ²&ª^§˜¨©cªÀ¯ °±{Áv¾© ²© ²&ª½·„´'Â&¸ © ²Ä̲¨ °cªL©c´Å© ²&ª½ªµ¶ ´ ·A© ²&ª³!ªµ© Â&¸MÆ Ç¼È=²ªLɸM°c©U̲Œ¨ °cª½ÁA¨ °(¶&¸M¾oÊ ªµËÆÄÌÅÈU±Q© ²&ª^° ª³!´'µ¶Í ¨VÊ ´'Â&¸ ª¶ÅËÆ¿Î$Ï8±© ²&ª© ²¾¸M¶ÑÐ ¸8¨ ¹½¹½¨© ¾o³!´Ò§´ Ð'¾˜³¨ §>±1Áv²¾o§ªU© ²ª(·„´'Â&¸ © ²Å̲¨ °cª›²¨ °=·„´•³Œ°cª¶¬´'µÓ§ª!Ô&¾o³¨ §¨ µ¶³!´ ¸ Ì°¶¨© ¨¥Ç¿È=²¾o°(§o¨ °c©X̲Œ¨ °cª^¾o§o§˜Â°c©c¸M¨©cª°U© ²ª³!Æ¥³§o¾o³½³8²¨¸M¨ ³!©cª¸b´ ·6Á´ ¸MÕľoµ © ²&ªÉª§o¶G±{° ¾oµ³!ª¾©^²Œ¨ °½¸ ª© Â&¸8µ&ª¶)©c´Ö¨+¹½¨ ×c´ ¸³!´'µ³!ª¸8µØ´ ·U© ²&ª¬É¸M°c©½Ã1ª¸M¾o´•¶G±€µ¨ ¹Lª§ÆÙˌŒ¾o§o¶¾oµÐÅ© ²&ª¬Ã´ Áª¸M·„§$¨ µ¶³!´'¹LøMª²&ªµ° ¾Ê ª ¶¾˜³!© ¾´'µ¨¸M¾ª°© ²¨©¿°cª¸8¾´'°ÛÚ$܂ÝÞ¨Ã̧˜¾o³¨© ¾´'µ°¼§o¾Õ ªÄÌÅÈßµ&ªª¶G±*¨ µ¶”²¨ °Û¸ ªÊ¥¾Ê ª¶ª¨¸M§Æø ´ Ã1´'° ¨ §o°·„´ ¸6ª!ԕ©c¸M¨ ³!© ¾˜µ&н§o¾oµ&Ð'Œ¾o°c© ¾o³=¾˜µ&·j´ ¸8¹½¨© ¾´'µ¼·j¸M´'¹à§˜¨¸ Ð ªXµ¨© Â&¸M¨ §1³!´ ¸ Ã1´ ¸M¨¥ÇÎA©6© ²ªX° ¨ ¹Lª© ¾o¹Lª ±G¾©*¨ §o°c´Û¾o§o§˜Â°c©c¸M¨©cª°$© ²&ª›ª!ԕ©cªµ©U©c´ÛÁv²¾o³8²¬¸ ª¨ §{øM´ Ð ¸ ª° °*²¨ °*Ë1ªªµÅ¹^¨ ¶&ªL¾oµ¬© ²ªÉª§˜¶Å¾oµÓ° ³8²Õ ªÆѨ¸ ª¨ °v¨ °$³!´'¹LÌÂ&© ¨© ¾o´'µ¨ §GÐ ¸M¨ ¹½¹^¨¸v¨ µ¶Ñ̨¸8° ¾oµ&Ð&Çá âäãbå6æ}çéèvêØëMå€ìçíè€î6ï$ð=æñìòíë å€ì1çéèAîvó6ðvæÈ=²&ªUÁ€´ ¸ ÕÛ´ ·#© ²&ªXɸ8°c©6̲¨ °cª(Á€¨ °v·j´¥³Â°cª¶Ñ´'µ¬¹½¨ ³M²¾˜µ&ªX©c¸M¨ µ°M§o¨© ¾´'µ+ô>ÌÅÈ$õ8njö&´'§˜§´VÁv¾˜µ&Ð^¨L·„ªÁ÷ª¨¸M§Æˌ¾¸8¶°±¾˜µ³§o¶¾˜µ&Ð(ø€´´ © ²¬¨ µ¶Ûùv¾o³8²&ªµ°ú&¾oµÊ ª°c© ¾Ð'¨© ¾´'µŒ°6¨ µ¶¼û ª¨Ê ª¸ú4°’¾oµ Í Âªµ© ¾o¨ §}¹Lª¹L´ ¸M¨ µŒ¶Â¹à´'µ©c¸M¨ µ°M§o¨© ¾´'µ´ ·«­-ü­Ñô`ÜQ´¥³ Õ ªX¨ µŒ¶¼ø€´•´ © ²G±G«­ ý ý'õ8±¸ ª°cª¨¸8³M²Û´'µÑڒ܊ÝÙË1ªÐ'¨ µÛ¾oµ^ª¨¸8µ&ª°c©6¾oµ© ²&ª›«­ ý¯ °ÇΒÂ&©c´'¹½¨© ¾o³©c¸M¨ µ° §˜¨© ¾´'µ¿·„¸ ´'¹þùv° °M¾o¨ µÑ©c´Ûÿeµ&Ð'§o¾˜° ²G±Œ¾oµÅ¨^Ê ª¸MÆѸM¶¾o¹½ªµ© ¨¸ ÆÛ·„´ ¸M¹þ¨ µ¶¬§o¾˜¹½¾©cª¶Ñª!ԕÒÃ1ª¸M¾o¹Lªµ©±#Á€¨ °›ª!Ô&²¾ˌ¾o©cª¶+¾oµ© ²&ª¼ÏCø6Ì¿Ò ’ª´ ¸ Ð ª©c´VÁ$µ ’ª¹L´'µ°c©c¸8¨© ¾´'µÙ´ ·(«­ ý-ü&ÇÄÈ=²&ª(×c´'Â&¸Mµ¨ §   
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`
`The work of the first phase was focused on machine translation (MT). Following a few early
`birds, including Booth and Richens’ investigations and Weaver’s influential memorandum on
`translation of 1949 (Locke and Booth, 1955), research on NLP began in earnest in the 1950s.
`Automatic translation from Russian to English, in a very rudimentary form and limited ex-
`periment, was exhibited in the IBM-Georgetown Demonstration of 1954. The journal MT
`(Mechanical Translation), the ancestor of Computational Linguistics, also began publication
`in 1954. Thefirst international conference on MT was held in 1952, the second in 1956 (the
`year of the first artificial intelligence conference); at the important Washington International
`Conference on Scientific Information of 1958 language processing was linked with information
`retrieval, for example in the use of a thesaurus, Minsky drew attention to artificial intelli-
`gence, and Luhn provided auto-abstracts (actually extracts) for one session’s papers. The
`Teddington International Conference on Machine Translation of Languages and Applied Lan-
`guage Analysis in 1961 was perhaps the high point of this first phase: it reported work done
`in many countries on many aspects of NLP including morphology, syntax and semantics, in
`interpretation and generation, and ranging from formal theory to hardware.
`This first phase was a period of enthusiasm and optimism. It is notable not only because
`those engaged attacked a very difficult NLP task, and so encountered the problemsof syntac-
`tic and semantic processing, and of linguistic variety, in all their force; they were seeking to
`use a new tool, computers, for non-numerical, data-processing purposes when data-processing
`itself was not well established. It is essential to remember how primitive the available com-
`puting resources were. This was the era of punched cards and batch processing. There were
`no suitable higher-level languages and programming was virtually all in assembler. Access
`to machines was often restricted; they had very limited storage, and were extremely slow.
`Plath (1967) reports processing speeds like 7 minutes for analysing long sentences, even with
`the most advanced algorithms and on the best machines then available. Vast amounts of
`programmingeffort were devoted to bit-packing to save space and time. It is remarkable how
`much was done with such poor resources, for example in grammar andlexicon building: some
`of the grammars and dictionaries of the early 1960s were very large even by current standards.
`Research in this period was thoroughly international, with considerable activity in the
`USSR as well as in the USA and Europe, and some in Japan. US grant funding increased
`after Sputnik 1, but the work had begun before. Russian and English were the dominant
`languages, but others, including Chinese, were involved (Booth, 1967; Hutchins, 1986, 2000).
`Though the period ended under the cloud of the 1966 ALPAC Report, most of those
`engaged were neither crooks nor bozos. Many came to NLP research with a background
`
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`experience, as at the Rand Corporation. There was indeed enough knowhow by now for some
`textbooks, like Hays (1967).
`There waslittle work, on the other hand, on some important problems that have since
`attracted attention, like anaphor resolution, since though text was being translated it was
`treated as a sequence of independent sentences, or on the function of language, since the work
`was mainly on single-source discourse. There waslittle attempt to incorporate world knowl-
`edge, and to relate this non-linguistic to linguistic knowledge, though some world knowledge
`was smuggled in under the heading of semantics. The belief, or challenge, was that one could
`get far enough with essentially linguistic, and therefore shallow, processing not involving rea-
`soning on world models. The research of this period did not produce any systems of scope or
`quality, though by the end of the 1960s there were MT production systems providing output
`of use to their customers (Hutchins, 1986). There was more merit in the work of the period,
`and more continuity, through individuals, with later effort, than subsequent myths allow,
`though the early literature was inaccessible and little used. But perhaps the best comment
`is Bledsoe’s at the International Joint Conference on Artificial Intelligence of 1985 (Bledsoe,
`1986) on the value, for artificial intelligence as a whole, of the early MT workers’ head-on
`attempt to do somethingreally hard.
`Work on the use of computers for literary and linguistic study also began in this period,
`but it has never been closely linked with that in NLP, though some common concerns have
`become more prominent recently.
`
`3 Phase 2: late 1960s to late 1970s
`
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`The second phase of NLP work wasartificial intelligence (AI)-flavoured, with much more
`emphasis on world knowledge and on its role in the construction and manipulation of mean-
`ing representations. Pioneering work influenced by AI on the problems of addressing and
`contructing data or knowledge bases began as early as 1961, with the BASEBALL question-
`answering system (Green et al., 1961). The actual input to these systems was restricted and
`the language processing involved very simple compared with contemporary MT analysis, but
`the systems described in Minsky (1968), and Raphael’s SIR in particular, recognised and
`provided for the need for inference on the knowledge base in interpreting and responding to
`language input.
`Woodset al.’s LUNAR (Woods, 1978) and Winograd’s SHRDLU (Winograd, 1973) were
`the natural successors of these systems, but they were widely seen at the time as represent-
`ing a step up in sophistication, in terms both of their linguistic and their task-processing
`capabilities. Though differing in many ways they shared a procedural style and were per-
`ceived as having an overall coherence as systems and a genuinely computational character.
`The dominant linguistic theory of the late 1960s, transformational grammar, was seen both
`as fundamentally unsuited to computation and particularly analysis, even though TG was
`formally oriented and there was at least one serious transformational parser, and as offering
`nothing on semantics, which had to be tackled for any actual NLP system. The computa-
`tional confidence illustrated by Woods’ and Winograd’s work, and the range of experiment it
`promoted, while drawing on previous work, is well shown by the varied research reported in
`Rustin (1973).
`The view that current linguistics had nothing to contribute, and the feeling that AI
`was liberating, were also apparent in Schank’s work (1980), which explicitly emphasised
`
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