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* Restructure tag maps for MorphAnalysis changes
Prepare tag maps for upcoming MorphAnalysis changes that allow
arbritrary features.
* Use default tag map rather than duplicating for ca / uk / vi
* Import tag map into defaults for ga
* Modify tag maps so all morphological fields and features are strings
* Move features from `"Other"` to the top level
* Rewrite tuples as strings separated by `","`
* Rewrite morph symbols for fr lemmatizer as strings
* Export MorphAnalysis under spacy.tokens
* Modify morphology to support arbitrary features
Modify `Morphology` and `MorphAnalysis` so that arbitrary features are
supported.
* Modify `MorphAnalysisC` so that it can support arbitrary features and
multiple values per field. `MorphAnalysisC` is redesigned to contain:
* key: hash of UD FEATS string of morphological features
* array of `MorphFeatureC` structs that each contain a hash of `Field`
and `Field=Value` for a given morphological feature, which makes it
possible to:
* find features by field
* represent multiple values for a given field
* `get_field()` is renamed to `get_by_field()` and is no longer `nogil`.
Instead a new helper function `get_n_by_field()` is `nogil` and returns
`n` features by field.
* `MorphAnalysis.get()` returns all possible values for a field as a
list of individual features such as `["Tense=Pres", "Tense=Past"]`.
* `MorphAnalysis`'s `str()` and `repr()` are the UD FEATS string.
* `Morphology.feats_to_dict()` converts a UD FEATS string to a dict
where:
* Each field has one entry in the dict
* Multiple values remain separated by a separator in the value string
* `Token.morph_` returns the UD FEATS string and you can set
`Token.morph_` with a UD FEATS string or with a tag map dict.
* Modify get_by_field to use np.ndarray
Modify `get_by_field()` to use np.ndarray. Remove `max_results` from
`get_n_by_field()` and always iterate over all the fields.
* Rewrite without MorphFeatureC
* Add shortcut for existing feats strings as keys
Add shortcut for existing feats strings as keys in `Morphology.add()`.
* Check for '_' as empty analysis when adding morphs
* Extend helper converters in Morphology
Add and extend helper converters that convert and normalize between:
* UD FEATS strings (`"Case=dat,gen|Number=sing"`)
* per-field dict of feats (`{"Case": "dat,gen", "Number": "sing"}`)
* list of individual features (`["Case=dat", "Case=gen",
"Number=sing"]`)
All converters sort fields and values where applicable.
286 lines
7.3 KiB
Python
286 lines
7.3 KiB
Python
from ...symbols import LEMMA, PRON_LEMMA
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# Used the table of pronouns at https://sv.wiktionary.org/wiki/deras
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MORPH_RULES = {
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"PRP": {
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"jag": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "One",
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"Number": "Sing",
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"Case": "Nom",
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},
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"mig": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "One",
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"Number": "Sing",
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"Case": "Acc",
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},
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"mej": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "One",
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"Number": "Sing",
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"Case": "Acc",
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},
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"du": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Two",
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"Number": "Sing",
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"Case": "Nom",
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},
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"han": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Three",
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"Number": "Sing",
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"Gender": "Masc",
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"Case": "Nom",
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},
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"honom": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Three",
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"Number": "Sing",
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"Gender": "Masc",
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"Case": "Acc",
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},
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"hon": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Three",
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"Number": "Sing",
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"Gender": "Fem",
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"Case": "Nom",
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},
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"henne": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Three",
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"Number": "Sing",
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"Gender": "Fem",
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"Case": "Acc",
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},
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"det": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Three",
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"Number": "Sing",
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"Gender": "Neut",
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},
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"vi": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "One",
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"Number": "Plur",
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"Case": "Nom",
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},
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"oss": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "One",
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"Number": "Plur",
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"Case": "Acc",
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},
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"ni": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Two",
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"Number": "Plur",
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"Case": "Nom",
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},
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"er": {LEMMA: PRON_LEMMA, "PronType": "Prs", "Person": "Two", "Number": "Plur"},
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"de": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Three",
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"Number": "Plur",
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"Case": "Nom",
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},
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"dom": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Three",
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"Number": "Plur",
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"Case": "Nom,Acc",
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},
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"dem": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Three",
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"Number": "Plur",
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"Case": "Acc",
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},
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"min": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "One",
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"Number": "Sing",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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"mitt": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "One",
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"Number": "Sing",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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"mina": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "One",
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"Number": "Plur",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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"din": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Two",
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"Number": "Sing",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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"ditt": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Two",
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"Number": "Sing",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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"dina": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Two",
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"Number": "Plur",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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"hans": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Two",
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"Number": "Sing,Plur",
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"Gender": "Masc",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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"hennes": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Two",
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"Number": "Sing,Plur",
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"Gender": "Fem",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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"dess": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Two",
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"Number": "Sing,Plur",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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"vår": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "One",
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"Number": "Plur",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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"våran": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "One",
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"Number": "Plur",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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"vårt": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "One",
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"Number": "Plur",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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"vårat": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "One",
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"Number": "Plur",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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"våra": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "One",
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"Number": "Plur",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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"eran": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Two",
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"Number": "Plur",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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"ert": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Two",
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"Number": "Plur",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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"erat": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Two",
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"Number": "Plur",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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"era": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Two",
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"Number": "Plur",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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"deras": {
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LEMMA: PRON_LEMMA,
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"PronType": "Prs",
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"Person": "Three",
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"Number": "Plur",
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"Poss": "Yes",
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"Reflex": "Yes",
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},
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},
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"VBZ": {
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"är": {
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"VerbForm": "Fin",
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"Person": "One,Two,Three",
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"Tense": "Pres",
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"Mood": "Ind",
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}
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},
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"VBP": {"är": {"VerbForm": "Fin", "Tense": "Pres", "Mood": "Ind"}},
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"VBD": {
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"var": {"VerbForm": "Fin", "Tense": "Past", "Number": "Sing"},
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"vart": {"VerbForm": "Fin", "Tense": "Past", "Number": "Plur"},
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},
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}
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