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# Topics

A page per concept of language technology: what it is in plain words, how Mova does it, and the cards of the papers on it from Mova's library, best first. The cards are also listed by [author](https://md.mova.elamur.ai/free/en/docs/papers/authors/) and on the [papers](https://md.mova.elamur.ai/free/en/docs/papers/) front.

- [𒀭](https://md.mova.elamur.ai/free/en/docs/papers/topics/akkadian-cuneiform-nlp/) — Akkadian and cuneiform NLP · The language of Babylon and Assyria and the wedge-shaped script it was written in. · 15 cards
- [🏷️](https://md.mova.elamur.ai/free/en/docs/papers/topics/named-entity-recognition/) — Named entity recognition · Finding the names in a text and saying what each names: a person, a place, an organization. · 10 cards
- [🧵](https://md.mova.elamur.ai/free/en/docs/papers/topics/discourse-analysis/) — Discourse analysis · How the sentences of a text hang together: what follows from what, and why. · 86 cards
- [💬](https://md.mova.elamur.ai/free/en/docs/papers/topics/speech-act-theory/) — Speech act theory · Saying as doing: asking, promising, ordering, thanking. · 34 cards
- [😉](https://md.mova.elamur.ai/free/en/docs/papers/topics/implicature/) — Implicature · What a speaker means beyond what the words say. · 19 cards
- [🔗](https://md.mova.elamur.ai/free/en/docs/papers/topics/coreference-resolution/) — Coreference resolution · Which words of a text name the same person or thing. · 96 cards
- [🔀](https://md.mova.elamur.ai/free/en/docs/papers/topics/word-sense-disambiguation/) — Word sense disambiguation · Choosing the meaning a word has in its sentence. · 22 cards
- [🌳](https://md.mova.elamur.ai/free/en/docs/papers/topics/dependency-parsing/) — Dependency parsing · Every word of a sentence attached to the word it depends on. · 98 cards
- [🌐](https://md.mova.elamur.ai/free/en/docs/papers/topics/universal-dependencies/) — Universal Dependencies · One way to annotate the grammar of every language. · 74 cards
- [🗂️](https://md.mova.elamur.ai/free/en/docs/papers/topics/treebanks/) — Treebanks · Corpora where every sentence comes with its grammatical tree. · 139 cards
- [🎭](https://md.mova.elamur.ai/free/en/docs/papers/topics/semantic-role-labeling/) — Semantic role labeling · Who did what to whom, where, when and why. · 46 cards
- [🔤](https://md.mova.elamur.ai/free/en/docs/papers/topics/part-of-speech-tagging/) — Part-of-speech tagging · Noun, verb, adjective: the part of speech of every word in its context. · 80 cards
- [🔁](https://md.mova.elamur.ai/free/en/docs/papers/topics/machine-translation/) — Machine translation · Translating text from one language to another by program. · 326 cards
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