wsd | A 78.5 % word sense disambiguator based on Transformers | Natural Language Processing library

This answer is composed based on the comment given for this SO post.

The number sequence followed by % is the lex_index. Lex index composed as follows.

ss_type:lex_filenum:lex_id:head_word:head_id

More information is in the WordNet documentation.

Bring Set msg = OA.CreateItem(olMailItem) into your second FOR loop. Then have a msgbox at the end to ask the user if they want to send the msg. If they do, send the msg. If they dont, display a second msg where the user has to click on continue before creating a new item – Zac yesterday

You can try the following XQuery. It is following a happy path.

"...There are many XML fields that doesn't even contain the records I would like to swap...". You never provided DDL and sample data population. You can always add a WHERE clause to the UPDATE statement to filter out not needed rows.

SQL

In this line (and the others):

Transfer learning, particularly models like Allen AI’s ELMO, OpenAI’s Open-GPT, and Google’s BERT allowed researchers to smash multiple benchmarks with minimal task-specific fine-tuning and provided the rest of the NLP community with pretrained models that could easily (with less data and less compute time) be fine-tuned and implemented to produce state of the art results.

these representations will help you accuratley retrieve results matching the customer's intent and contextual meaning(), even if there's no keyword or phrase overlap.

To start off, embeddings are simply (moderately) low dimensional representations of a point in a higher dimensional vector space.

By translating a word to an embedding it becomes possible to model the semantic importance of a word in a numeric form and thus perform mathematical operations on it.

When this was first possible by the word2vec model it was an amazing breakthrough. From there, many more advanced models surfaced which not only captured a static semantic meaning but also a contextualized meaning. For instance, consider the two sentences below:

URLSession to decode

URLSession does no such thing. You want to use Decodable.

Q1: Yes.

Q2: That's an array, so you will need a struct describing each entry.

A very good starting point is to paste your JSON data into app.quicktype.io and use the code/structs that it generates for you.

What I only want is the "obsrvalue"'s value which is under the category name REH (the pink box).

Use .filter or .first(where:)` on your parsed result.

Apply a while loop to go through all the lines.

I looked at the source for the lesk function, and if it is not explicitly passed a synsets argument it creates one by calling wordnet.synsets(ambiguous_word), but it doesn't pass a language option or anything.

If no synset is found for the word it just returns None hence the error you're getting. You can explicitly pass a synset like:

Q : " Do I also need multiple contexts? "

No, you need not.

_{In case one has never worked with ZeroMQ,
one may here enjoy to first look at "ZeroMQ: Principles in less than Five Seconds"
before diving into further details}

Q : " How is this done? "