Part of Speech Tagger
Uses hidden markov models (HMM's) to classify parts of speech in sentences. Pretty basic implementation but CV shows ~95% accuracy which is pretty cool.
For the training data, we use the Brown corpus, using Natural Language Processing with Python as guidance.
Here are some examples of tags and their expansions:
| Tag | Meaning | Examples |
|---|---|---|
| ADJ | adjective | new, good, high, special, big, local |
| ADV | adverb | really, already, still, early, now |
| CNJ | conjunction | and, or, but, if, while, although |
| DET | determiner | the, a, some, most, every, no |
| EX | existential | there, there's |
| FW | foreign word | dolce, ersatz, esprit, quo, maitre |
App is currently hosted at: http://pos-tagger.herokuapp.com/ (endpoint: "api/v1/tagger", query param "?value=")
Example: http://pos-tagger.herokuapp.com/api/v1/tagger?value=hello%20my%20name%20is%20xinran