This is still a research topic in linguistics. A quick google search brings up a couple of papers that might be useful:
Identifying Metaphor Hierarchies in a Corpus Analysis of Finance Articles
Metaphor Identification in Large Texts Corpora
However, you probably won't get an off-the-shelf tool that recognises metaphors for you.
To add more details, the ...
You might be referring to Semantic role labeling. SRL is the task of assigning labels to words or phrases in a sentence that shows their semantic role in that sentence.
In your example CV was hit by IV, the task is to identify the verb "hit" carried out by the actor "CV" affected "IV" the recipient.
Note: If you're only interested in the syntactic ...
In grammar, a predicate-argument relationship is one which is implied from text but not expressed in the syntactic structure. (Asher S)
Predicate logic or first order logic is a collection of formal systems used in mathematics, philosophy, linguistics and computer science.
The NLP community is interested in recognizing, representing and classifying ...
It all depends on your architecture.
What a chatbot is made of?
Most of the current commercial AI chatbots have an architecture somehow like this:
│ │ │ │ │ ...
While it is certainly possible to have NLP algorithms ending up in infinite loops, chatbots will typically not be affected by this.
A first-year pitfall you learn is in the construction of grammars. If you do a top-down analysis of a sentence, the following grammar rule will send it into an infinite loop:
NP -> NP of NP | det N | N
This allows a noun ...
You can generally identify the mood of a verb by looking at grammatical structures; you don't need any language model for it. The three major moods in English are declarative, interrogative, and imperative. Assuming English is the language you will be working with, here are some questions:
Does he like coffee?
Is this a piece of chocolate?
When did you go ...
The LSTM seq2seq model typically used for language translation actually can output multiple variations, and does in many implementations.
The decoder stage outputs confidence/probabilities for each word, and it is possible to run the decoder multiple times, taking different samples on each run.
Not only is it possible, but this is actually done by ...
This seems not easy for NLP. I doubt that state-of-the-art NLP tools can reliably determine the correct hierarchical structure of independent clauses. Examples below.
The Berkeley parser gets it basically right in the sense that it can put its late and I'm tired on parallel, and they together on parallel with the weekend. But still not perfect (the weekend ...
your question is a very similar to "turing-test". you could narrate a simple story and ask questions based on that , considering the state-of-art algorithms in "question-answering" are still far beyond human skills.