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Amharic (amh)

Contents

  • amh: inflection tables for Amharic (ISO 639-3 amh)
  • amh.args: a UniMorph 4.0 compatible verion of amh
  • amh.gloss: English glosses for the lemmas in amh
  • README.md: this file

Data

All data were generated using the Amharic morphological generator in HornMorpho, described in Gasser (2013).

Decisions about lemma frequency and subcategorization were based on Biniam Gebremichael's Amharic word list.

Common orthographic variants of lemmas and common variant plural forms of nouns are included. In these cases, the variants are distinguished with the features LGSPEC1 and LGSPEC2. Predictable orthographic variants are not included. These include alternate representations of labialized consonants (ቆ/ቈ, ቁ/ቍ, ፏ/ፍዋ, etc.), the two ways of writing the vowel ɨ/i before y (e.g., ጅያ/ጂያ), and the common replacement of ው with ዉ.

The total number of lemmas is 2,465: V 670, N 1599, ADJ 196.

Verbs

Although the formation of the passive-reflexive, causative, reciprocal, and frequentative from bare roots is relatively productive, many roots fail to appear in the basic, underived form, in which case the morphologically passive-reflexive or causative form is not semantically or syntactically passive-reflexive or causative (for example, "passive-reflexive" ተቀመጠ 'sit', "causative" አለቀሰ 'cry'). For this reason, each of these derived forms of a root is treated as a separate lemma, and only those appearing in the word list have been included. For example, based on the root 'break', there are the following lemmas in the repository: ሰበረ 'break', ተሰበረ 'be broken', ሰባበረ 'break repeatedly'. Other possible forms derived from this root are not included.

Verb lemmas appear in all of the major tense-aspect categories and the infinitive:

  • perfective (UM: PFV)
  • finite (UM: IPFV) and non-finite imperfective (UM: NFIN;IPFV)
  • gerundive (UM: V.CVB)
  • present perfect (UM: PRF)
  • jussive-imperative (UM: IMP)
  • infinitive (UM: V.MSDR).

Features for the copula (ነው) and verb of existence (ለአ) include "present" (PRS).

Verb lemmas are divided into two subcategories based on their occurrence with different subjects or with only (or mainly) third person singular masculine subjects. Lemmas in the first ("personal") category are further divided into reciprocal verbs, which only appear with plural subjects, and all other verbs, which appear with all eight subject agreement affixes. Lemmas in the "impersonal" category only appear with third person singular masculine affixes.

Not included in the paradigms: object suffixes, negative prefixes/suffixes, relative prefixes, prepositional/conjunctive prefixes.

Nouns and adjectives

Nouns and adjectives share most of their morphology and are often not clearly distinguished.

Noun and adjective lemmas are divided into five categories based on their occurrence with the masculine and feminine definite suffixes, with the plural form, and with possessive suffixes. Those classified as adjectives admit both masculine and feminine definite suffixes and plural forms and have English adjective glosses. Since most nouns do have inherent gender, gender is only specified for singular nouns with one of the gender-specific definite suffixes. Gender is not distinguished for plural nouns and adjectives.

Not included in the paradigms: prepositional/case prefixes and the accusative suffix.

Annotator

Michael Gasser

Paradigm Samples

Noun (including plural and possessive suffixes)

ቃል /k'al/ 'word'

ቃል	ቃሉ	N;DEF;MASC
ቃል	ቃሉ	N;PSS3SM
ቃል	ቃላቱ	N;DEF;PL
ቃል	ቃላቱ	N;PL;PSS3SM
ቃል	ቃላታቸው	N;PL;PSS3P
ቃል	ቃላታችሁ	N;PL;PSS2P
ቃል	ቃላታችን	N;PL;PSS1P
ቃል	ቃላቴ	N;PL;PSS1S
ቃል	ቃላት	N;PL
ቃል	ቃላትህ	N;PL;PSS2SM
ቃል	ቃላትሽ	N;PL;PSS2SF
ቃል	ቃላትዎ	N;PL;FORM;PSS2S
ቃል	ቃላቷ	N;PL;PSS3SF
ቃል	ቃላቸው	N;PSS3P
ቃል	ቃላችሁ	N;PSS2P
ቃል	ቃላችን	N;PSS1P
ቃል	ቃሌ	N;PSS1S
ቃል	ቃል	N
ቃል	ቃልህ	N;PSS2SM
ቃል	ቃልሽ	N;PSS2SF
ቃል	ቃልዎ	N;FORM;PSS2S
ቃል	ቃሎቹ	N;DEF;PL;LGSPEC1
ቃል	ቃሎቹ	N;PL;PSS3SM;LGSPEC1
ቃል	ቃሎቻቸው	N;PL;PSS3P;LGSPEC1
ቃል	ቃሎቻችሁ	N;PL;PSS2P;LGSPEC1
ቃል	ቃሎቻችን	N;PL;PSS1P;LGSPEC1
ቃል	ቃሎቼ	N;PL;PSS1S;LGSPEC1
ቃል	ቃሎች	N;PL;LGSPEC1
ቃል	ቃሎችህ	N;PL;PSS2SM;LGSPEC1
ቃል	ቃሎችሽ	N;PL;PSS2SF;LGSPEC1
ቃል	ቃሎችዎ	N;PL;FORM;PSS2S;LGSPEC1
ቃል	ቃሎቿ	N;PL;PSS3SF;LGSPEC1
ቃል	ቃሏ	N;DEF;FEM
ቃል	ቃሏ	N;PSS3SF

Verb (all subjects)

ተቀመጠ /tǝk'ǝmmǝt'ǝ/ 'sit'

ተቀመጠ	ተቀምጠን	V.CVB;1;PL
ተቀመጠ	ተቀምጬ	V.CVB;1;SG
ተቀመጠ	ተቀምጣችሁ	V.CVB;2;PL
ተቀመጠ	ተቀምጠሽ	V.CVB;2;SG;FEM
ተቀመጠ	ተቀምጠህ	V.CVB;2;SG;MASC
ተቀመጠ	ተቀምጠው	V.CVB;3;PL
ተቀመጠ	ተቀምጣ	V.CVB;3;SG;FEM
ተቀመጠ	ተቀምጦ	V.CVB;3;SG;MASC
ተቀመጠ	መቀመጥ	V.MSDR
ተቀመጠ	እንቀመጥ	V;IMP;1;PL
ተቀመጠ	ልቀመጥ	V;IMP;1;SG
ተቀመጠ	ተቀመጡ	V;IMP;2;PL
ተቀመጠ	ተቀመጪ	V;IMP;2;SG;FEM
ተቀመጠ	ተቀመጥ	V;IMP;2;SG;MASC
ተቀመጠ	ይቀመጡ	V;IMP;3;PL
ተቀመጠ	ትቀመጥ	V;IMP;3;SG;FEM
ተቀመጠ	ይቀመጥ	V;IMP;3;SG;MASC
ተቀመጠ	እንቀመጣለን	V;IPFV;1;PL
ተቀመጠ	እቀመጣለሁ	V;IPFV;1;SG
ተቀመጠ	ትቀመጣላችሁ	V;IPFV;2;PL
ተቀመጠ	ትቀመጫለሽ	V;IPFV;2;SG;FEM
ተቀመጠ	ትቀመጣለህ	V;IPFV;2;SG;MASC
ተቀመጠ	ይቀመጣሉ	V;IPFV;3;PL
ተቀመጠ	ትቀመጣለች	V;IPFV;3;SG;FEM
ተቀመጠ	ይቀመጣል	V;IPFV;3;SG;MASC
ተቀመጠ	እንቀመጥ	V;IPFV;NFIN;1;PL
ተቀመጠ	እቀመጥ	V;IPFV;NFIN;1;SG
ተቀመጠ	ትቀመጡ	V;IPFV;NFIN;2;PL
ተቀመጠ	ትቀመጪ	V;IPFV;NFIN;2;SG;FEM
ተቀመጠ	ትቀመጥ	V;IPFV;NFIN;2;SG;MASC
ተቀመጠ	ይቀመጡ	V;IPFV;NFIN;3;PL
ተቀመጠ	ትቀመጥ	V;IPFV;NFIN;3;SG;FEM
ተቀመጠ	ይቀመጥ	V;IPFV;NFIN;3;SG;MASC
ተቀመጠ	ተቀመጥን	V;PFV;1;PL
ተቀመጠ	ተቀመጥኩ	V;PFV;1;SG
ተቀመጠ	ተቀመጣችሁ	V;PFV;2;PL
ተቀመጠ	ተቀመጥሽ	V;PFV;2;SG;FEM
ተቀመጠ	ተቀመጥክ	V;PFV;2;SG;MASC
ተቀመጠ	ተቀመጡ	V;PFV;3;PL
ተቀመጠ	ተቀመጠች	V;PFV;3;SG;FEM
ተቀመጠ	ተቀመጠ	V;PFV;3;SG;MASC
ተቀመጠ	ተቀምጠናል	V;PRF;1;PL
ተቀመጠ	ተቀምጫለሁ	V;PRF;1;SG
ተቀመጠ	ተቀምጣችኋል	V;PRF;2;PL
ተቀመጠ	ተቀምጠሻል	V;PRF;2;SG;FEM
ተቀመጠ	ተቀምጠሀል	V;PRF;2;SG;MASC
ተቀመጠ	ተቀምጠዋል	V;PRF;3;PL
ተቀመጠ	ተቀምጣለች	V;PRF;3;SG;FEM
ተቀመጠ	ተቀምጧል	V;PRF;3;SG;MASC

License

References

	@inproceedings{pimentel-ryskina-etal-2021-sigmorphon,
    title = "SIGMORPHON 2021 Shared Task on Morphological Reinflection: Generalization Across Languages",
    author = "Pimentel, Tiago  and
      Ryskina, Maria  and
      Mielke, Sabrina J.  and
      Wu, Shijie  and
      Chodroff, Eleanor  and
      Leonard, Brian  and
      Nicolai, Garrett  and
      Ghanggo Ate, Yustinus  and
      Khalifa, Salam  and
      Habash, Nizar  and
      El-Khaissi, Charbel  and
      Goldman, Omer  and
      Gasser, Michael  and
      Lane, William  and
      Coler, Matt  and
      Oncevay, Arturo  and
      Montoya Samame, Jaime Rafael  and
      Silva Villegas, Gema Celeste  and
      Ek, Adam  and
      Bernardy, Jean-Philippe  and
      Shcherbakov, Andrey  and
      Bayyr-ool, Aziyana  and
      Sheifer, Karina  and
      Ganieva, Sofya  and
      Plugaryov, Matvey  and
      Klyachko, Elena  and
      Salehi, Ali  and
      Krizhanovsky, Andrew  and
      Krizhanovsky, Natalia  and
      Vania, Clara  and
      Ivanova, Sardana  and
      Salchak, Aelita  and
      Straughn, Christopher  and
      Liu, Zoey  and
      Washington, Jonathan North  and
      Ataman, Duygu  and
      Kiera{\'s}, Witold  and
      Woli{\'n}ski, Marcin  and
      Suhardijanto, Totok  and
      Stoehr, Niklas  and
      Nuriah, Zahroh  and
      Ratan, Shyam  and
      Tyers, Francis M.  and
      Ponti, Edoardo M.  and
      Aiton, Grant  and
      Hatcher, Richard J.  and
      Prud'hommeaux, Emily  and
      Kumar, Ritesh  and
      Hulden, Mans  and
      Barta, Botond  and
      Lakatos, Dorina  and
      Szolnok, G{\'a}bor  and
      {\'A}cs, Judit  and
      Raj, Mohit  and
      Yarowsky, David  and
      Cotterell, Ryan  and
      Ambridge, Ben  and
      Vylomova, Ekaterina",
    booktitle = "Proceedings of the 18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology",
    month = aug,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.sigmorphon-1.25",
    doi = "10.18653/v1/2021.sigmorphon-1.25",
    pages = "229--259",
    abstract = "This year's iteration of the SIGMORPHON Shared Task on morphological reinflection focuses on typological diversity and cross-lingual variation of morphosyntactic features. In terms of the task, we enrich UniMorph with new data for 32 languages from 13 language families, with most of them being under-resourced: Kunwinjku, Classical Syriac, Arabic (Modern Standard, Egyptian, Gulf), Hebrew, Amharic, Aymara, Magahi, Braj, Kurdish (Central, Northern, Southern), Polish, Karelian, Livvi, Ludic, Veps, V{\~o}ro, Evenki, Xibe, Tuvan, Sakha, Turkish, Indonesian, Kodi, Seneca, Ash{\'a}ninka, Yanesha, Chukchi, Itelmen, Eibela. We evaluate six systems on the new data and conduct an extensive error analysis of the systems' predictions. Transformer-based models generally demonstrate superior performance on the majority of languages, achieving {\textgreater}90{\%} accuracy on 65{\%} of them. The languages on which systems yielded low accuracy are mainly under-resourced, with a limited amount of data. Most errors made by the systems are due to allomorphy, honorificity, and form variation. In addition, we observe that systems especially struggle to inflect multiword lemmas. The systems also produce misspelled forms or end up in repetitive loops (e.g., RNN-based models). Finally, we report a large drop in systems' performance on previously unseen lemmas.",
}