This a follow-up of previous discussions we had to decide if a feature must be instanciated or not (the last one concerning the Voice feature in English, see #290).
First, some features are features associated to inflectional morphemes, while others are lexical features. Examples of lexical features are Gender, Number and Person on pronouns in English, while inflectional feature are Number and Person on the verb agreeing with its subject:
she PRON, Gender[lex]=Fem, Number[lex]=Sing, Person[lex]=3
wants VERB, VerbForm[infl]=Fin, Tense[infl]=Pres, Number[infl]=Sing, Person[infl]=3
Another example is the Gender agreement of the adjective and articles with the noun in French. Gender is lexical feature of NOUNs (Gender[lex]), while Gender is an inflectional feature on ADJs or DETs (Gender[infl]):
la DET, Gloss=the:SG.FEM, Definite[lex]=Def, Gender[infl]=Fem, Number[infl]=Sing, PronType[lex]=Art
table NOUN, Gloss=table:SG, Gender[lex]=Fem, Number[infl]=Sing
blanche ADJ, Gloss=white:SG:FEM, Gender[infl]=Fem, Number[infl]=Sing
Note that Definiteness is a lexical feature, while Number is an inflectional feature on NOUNs, ADJs and articles (it is a lexical feature on most other DETs). PronType is an inherently lexical feature.
But there is a third use of morphosyntactic features: the denominative use. For instance, English has two participles which are the so-called present and past participles. The English treebank use the features Tense=Pres and Tense=Past to distinguish the two participles. It is quite problematic because these participles have more aspectual values than temporal:
driven VERB, VerbForm[infl]=Part, Tense[denom]=Past, Aspect[infl]=Imp
driving VERB, VerbForm[infl]=Part, Tense[denom]=Pres, Aspect[infl]=Prog
Second, in some case, an inflectional feature is not instantiated on a given lexeme. For instance, French has many ADJs, which do not show variation in Gender, such as rouge ‘red’, facile ‘easy’, etc. Nevertheless, the value can generally be deduced from the context. For the French treebanks, we thus have instantiated the Gender feature each time its value could be deduced from the context. This could be indicated on the value:
table NOUN, Gloss=table:SG, Gender[lex]=Fem, Number[infl]=Sing
rouge ADJ, Gloss=red:SG, Gender[infl]=Fem[ctxt], Number[infl]=Sing
English treebanks contain a lot of contextual values (due to the very poor inflectional morphology of English). For instance, every -ing verbal form can be VerbForm=Part or VerbForm=Ger. This can only be deduced from the context: not any English verb has a different form for the present participle and the gerund. “Only-contextual features" could be distinguished:
driving VERB, VerbForm[infl]=Part[ctxt], Tense[denom]=Pres, Aspect[infl]=Prog[only-ctxt]
driving VERB, VerbForm[infl]=Ger[only-ctxt]
Note that VerbForm=Part is just [ctxt] because the value is marked for past participles of some verbs (those distinguishing past participles and preterit). For past participles of transitive verbs, we have an opposition between imperfect forms (she has driven the car) and passive forms (the car was driven):
driven VERB, VerbForm[infl]=Part, Tense[denom]=Past, Aspect[infl]=Imp[ctxt]
driven VERB, VerbForm[infl]=Part, Tense[denom]=Past, Voice[infl]=Pass[only-ctxt]
The bare form of the verb is also ambiguous and can only be disambiguated contextually:
drive VERB, VerbForm[infl]=Inf[only-ctxt]
drive VERB, VerbForm[infl]=Fin[ctxt], Tense[infl]=Pres[ctxt], Number[infl]=Plur[ctxt], Person[infl]=1[ctxt]
Note that the value VerbForm=Inf is only contextual [only-ctxt], but not the value VerbForm=Fin, since finiteness is marked for the 3SG present form, as well as for the past form of some verbs.
drives VERB, VerbForm[infl]=Fin, Tense[infl]=Pres, Number[infl]=Sing, Person[infl]=3
drove VERB, VerbForm[infl]=Fin, Tense[infl]=Past, Number[infl]=Sing[ctxt], Person[infl]=3[ctxt]
It means that we can distinguish features for which some values can be marked (VerbForm, Tense, etc.) and features for which all values are contextual (Voice).
Of course it would be too costly to add the status of features and values to each occurrence, but it would be useful for people exploiting a treebank to know the status of features and values. We could ask in the guidelines associated with the validator whether a feature is inflectional [infl], lexical [lex] or denominative [denom]. Maybe also if the feature has values which are only contextual [only-ctxt].
Such information would be very useful for linguists exploiting the treebanks. If we currently study noun-adjective Gender agreement in French, it would be difficult with only the treebank to know when this agreement is really effective. Same thing with the verb-subject Person agreement in English. And if we study Tense in English (without any knowledge of the language), we would have strange results due to the Tense feature on participles.
This a follow-up of previous discussions we had to decide if a feature must be instanciated or not (the last one concerning the
Voicefeature in English, see #290).First, some features are features associated to inflectional morphemes, while others are lexical features. Examples of lexical features are
Gender,NumberandPersonon pronouns in English, while inflectional feature areNumberandPersonon the verb agreeing with its subject:Another example is the Gender agreement of the adjective and articles with the noun in French.
Genderis lexical feature of NOUNs (Gender[lex]), whileGenderis an inflectional feature on ADJs or DETs (Gender[infl]):Note that Definiteness is a lexical feature, while Number is an inflectional feature on NOUNs, ADJs and articles (it is a lexical feature on most other DETs). PronType is an inherently lexical feature.
But there is a third use of morphosyntactic features: the denominative use. For instance, English has two participles which are the so-called present and past participles. The English treebank use the features
Tense=PresandTense=Pastto distinguish the two participles. It is quite problematic because these participles have more aspectual values than temporal:Second, in some case, an inflectional feature is not instantiated on a given lexeme. For instance, French has many ADJs, which do not show variation in Gender, such as rouge ‘red’, facile ‘easy’, etc. Nevertheless, the value can generally be deduced from the context. For the French treebanks, we thus have instantiated the
Genderfeature each time its value could be deduced from the context. This could be indicated on the value:English treebanks contain a lot of contextual values (due to the very poor inflectional morphology of English). For instance, every -ing verbal form can be
VerbForm=PartorVerbForm=Ger. This can only be deduced from the context: not any English verb has a different form for the present participle and the gerund. “Only-contextual features" could be distinguished:Note that
VerbForm=Partis just[ctxt]because the value is marked for past participles of some verbs (those distinguishing past participles and preterit). For past participles of transitive verbs, we have an opposition between imperfect forms (she has driven the car) and passive forms (the car was driven):The bare form of the verb is also ambiguous and can only be disambiguated contextually:
Note that the value
VerbForm=Infis only contextual[only-ctxt], but not the valueVerbForm=Fin, since finiteness is marked for the 3SG present form, as well as for the past form of some verbs.It means that we can distinguish features for which some values can be marked (
VerbForm,Tense, etc.) and features for which all values are contextual (Voice).Of course it would be too costly to add the status of features and values to each occurrence, but it would be useful for people exploiting a treebank to know the status of features and values. We could ask in the guidelines associated with the validator whether a feature is inflectional
[infl], lexical[lex]or denominative[denom]. Maybe also if the feature has values which are only contextual[only-ctxt].Such information would be very useful for linguists exploiting the treebanks. If we currently study noun-adjective Gender agreement in French, it would be difficult with only the treebank to know when this agreement is really effective. Same thing with the verb-subject Person agreement in English. And if we study Tense in English (without any knowledge of the language), we would have strange results due to the Tense feature on participles.