Citations:non-lemma


 * 1965, Nagoya Mathematical Journal, volume XXVI, page 82:
 * For non-lemma (ɑ), we can take n as 0.
 * 1991 September, Lewis P. Shapiro et al., “Verb effects during sentence processing” in the , volume XVII, № 5, pages 986–987:
 * According to Schmauder (1991) they had a narrow range of frequency of occurrence (our nonlemma count yields an average of 68; Francis & Kucera, 1982).
 * 1995, Peter John Gentry, The Asterisked Materials in the Greek Job,, ISSN 1044‒6761, ISBN 0788500937 (10), ISBN 9780788500930 (13), :
 * Since the wording of the lemma differs from the non-lemma materials they cannot both be θʹ. In 18:15a the only difference is that the lemma has [Greek] for [Hebrew] in the parent text while the non-lemma has [Greek].
 * 1996, David L. Blank, Ammonius: On Aristotle On Interpretation 1–8, Bloomsbury (first paperback edition, 2014), ISBN 9781472558442, “Index of Passages Cited”, :
 * &#91; A ristotle Int.&#93; (non-lemma citations)
 * 1997, Michael Cahill, Scriptores Celtigenae: Pars II (Corpus Christianorum: Series Latina, volume LXXXII),, :
 * That this is to be rated as an error is confirmed by the fact that the same phrase from Mark 1,15 is quoted as “credite euangelio” at the very beginning of the Commentary in a non-lemma setting (1,5); “cum uenient” for “conueniunt” (Mark 7,1) – a type of error found more than once in A; “adueniens” for “et ueniens” (Mark 9,13); “exiuit” for “exi” (Mark 9,24); “adprofiscente” for “et profiscente” […]
 * 1998, , volume XXXVIII, issues vii–ix, :
 * Their knowledge scores were higher; this was also true in a later timed experiment, in which 12 Lemma programmers were compared with nine non-Lemma programmers.
 * 1999, David Alan Plaisted and Yunshan Zhu, The Efficiency of Theorem Proving Strategies: A Comparative and Asymptotic Analysis, /: Friedr. Vieweg & Sohn Verlagsgesellschaft mbH (second edition), ISSN 0949‒5665, ISBN 9783528155742, e-&zwnj;ISBN 9783663078470, § 1.5.14, :
 * Therefore, each call to a non-lemma procedure and each return from a non-lemma procedure either increase the size of the stack or increase the number of lemmas Let N be the sum of the stack size and twice the number of lemmas. Then N increases by 1 whenever a non-lemma procedure is called or returns successfully.
 * 2000, Arantxa Diaz de Ilarraza et al., Building a Lexicon for an English–Basque Machine Translation System from heterogeneous wide coverage dictionaries, § 5.1, page 4:
 * We identified five error sources: Non-lemmas: The word supplied by the lexical transfer module is an inflected word and not a lemma; for that reason, it is not possible to use it in generation.
 * ibidem, Table 2:
 * Prep. … Prenominal adjectives … Non lemmas … Basque multiword … English multiwords … English unknown … Others 11% … 21% … 7% … 5% … 17% … 16% … 21%
 * 2002, Christian Lehmann, “Structure of a comprehensive presentation of a language” in Basic Materials in Minority Languages, ed. Tasaku Tsunoda, § 4.3, page 17?:
 * If the database is to be printed out in the form of a dictionary, non-lemmas can be generated from the items contained in these fields.
 * 2002, Marinella Cappelletti et al., “Why semantic dementia drives you to the dogs (but not to the horses): A theoretical account” in Cognitive Neuropsychology, volume XIX, № 6, page 498/2:
 * However, the evidence presented here does not enable us to decide between the lemma and the nonlemma accounts.
 * 2003, Jean Rittmueller, Liber Questionum in Evangeliis (Corpus Christianorum: Series Latina, volume CVIII),, ISBN 2503030009 (10), ISBN 9782503030005 (13), :
 * A diple once marks a non-lemma biblical citation from Mt 26, 38 (Sustinete et uigilate) at ſ. Crb7.
 * ibidem, :
 * Occasionally, non-lemma “capitals at the beginning of sentences … have a daub of red”.
 * 2004, Walid A. Saleh, The Formation of the Classical Tafsīr Tradition: The Qurʾān Commentary of Al-Thaʿlabī (d. 427/1035), Koninklĳke Brill, ISSN 1567‒2808, ISBN 9004127771, chapter vi, § F, :
 * Al-Ṭabarī did not interrupt the flow of the commentary proper to discuss any non-lemma related matter.
 * 2007, Ruiqiang Zhang and Eiichiro Sumita, “Boosting Statistical Machine Translation by Lemmatization and Linear Interpolation” in ACL 2007: Proceedings of the Interactive Poster and Demonstration Sessions, June 25–27, 2007, Prague, Czech Republic, § 3.1, caption to Table 2, :
 * Table 2: Statistical significance test in terms of BLEU: sys1&#61;non-lemma, sys2&#61;lemma
 * ibidem, § 4, :
 * For example, phrase translation model p(e&#124;f) can be calculated as, [¶] p(e&#124;f) &#61; ɑ₁pₗ(e&#124;f) + ɑ₂pₙₗ(e&#124;f) [¶] where pₗ(e&#124;f) and pₙₗ(e&#124;f) is the phrase translation models corresponding to the lemmatization system and non-lemma system. ɑ₁ + ɑ₂ &#61; 1.
 * ibidem, Table 4, :
 * [ ] … lemma … nonlemma … interpolation open track … 0.1938 … 0.1993 … 0.2054
 * 2009, Marek Rei, Adaptive Interactive Information Extraction (MPhil in Computer Speech, Text and Internet Technology: Dissertation),, § 2.2, page 11:
 * The lemma ID in a relation may also be a negative number, in which case it represents a mapping to a non-lemma slot value – it would correspond to a value like that, to, etc.
 * 2009, Vincent Vandeghinste, “Scaling up a hybrid MT system: From low to full resources” in Evaluation of Translation Technology (Linguistica Antverpiensia New Series – Themes in Translation Studies VIII), eds. and Véronique Hoste, VUB Press, ISBN 9789054876823, part I, chapter iii, § 3.1, :
 * Part-of-Speech Tag mapping rules which convert the source language tags (Van Eynde, 2005) into target language tags are used to translate the non-lemma features of the source language tags (singular vs. plural, present vs. past, etc) into features of the target language tag (for instance, the Dutch tag the Dutch tag WW(pv,tgw,ev) is converted into VVB).
 * 2010, Rufus H. Gouws, “Fixed word combinations as second level treatment units in dictionaries” in Feste Wortverbindungen und Lexikographie: Kolloquium zur Lexikographie und Wörterbuchforschung, ed. Peter Ďurčo, Walter de Gruyter GmbH & Co. KG, ISSN 0175‒9264, ISBN 9783110234053, e-&zwnj;ISBN 9783110234060, chapter vi, § 3.1, :
 * Access to the treatment of the lemma does not initially proceed via the lemma sign but via a non-lemma reduced guiding element, i.e. a lemma part in the lemma extemal article entrance position.
 * 2010 March 19th, “cayorodriguez” (username), “Lemmatization module in NLTK” in, :
 * Initialize lemmatizer by providing dictionary file. If unknown, leave as non lemmata not found.
 * 2011, Bart Jacobs et al., “VeriFast: A Powerful, Sound, Predictable, Fast Verifier for C and Java” in NASA Formal Methods: Third International Symposium, NFM 2011, Pasadena, CA, USA, April 2011 – Proceedings, eds. Mihaela Bobaru et al., Springer-Verlag Berlin–Heidelberg, ISSN 0302‒9743, e-&zwnj;ISSN 1611‒3349, ISBN 9783642203978, e-&zwnj;ISBN 9783642203985, part II, chapter iv, § 4, pages 52–53:
 * A simple approach to ensure termination of lemma functions in the presence of lemma function pointers would be to allow lemma function pointer calls only in non-lemma functions.
 * ibidem, :
 * Non-lemma functions may produce lemma function pointer chunks arbitrarily.
 * 2011, Karin Harbusch and István Bátori, “Clausal Coordinate Ellipsis (CCE) in Hungarian compared to CCE in Dutch, German, and Estonian” in Approaches to Hungarian, volume XIII: Papers from the 2011 Lund Conference, eds. Johan Brandtler et al., (2013), ISBN 9789027204837 (hardback), e-&zwnj;ISBN 9789027271471, chapter iii, § 3.1, :
 * Elision of the wordform-identical Object das Fahrrad ‘the bike’ is “blocked” by the preceding non-lemma-identical Modifiers (‘expertly’ vs. ‘diligently’).
 * 2012 January 9th–13th, Maciej Piasecki et al., “Automated Generation of Derivative Relations in the Wordnet Expansion Perspective” in GWC 2012: Proceedings of the 6th International Global Wordnet Conference, January 9–13, 2012, Matsue, Japan, eds. and, § 4.2, page 278/1:
 * Morphological filtering limits the intrinsic lexical over-generation of the guessers and is always used. Very often non-words or non-lemmas are generated as potential derivative bases, especially for input lemmas that are not derivatives.
 * 2012 May 21st–27th, Maciej Piasecki et al., “Recognition of Polish Derivational Relations Based on Supervised Learning Scheme” in LREC 2012, § 2.2, page 918/2:
 * In step 3, non-words or non-lemmas, that are often generated by the guesser modules, are filtered out from the result. Morphological filtering limits the intrinsic lexical over-generation of the guessers. Very often non-words or non-lemmas are generated as potential derivative bases, especially for input lemmas that are not derivatives.