3 Vocabulary Words In A Sentence

[Lawana Stuckert]

Learningnew words and their meanings along with how to fit them in a context is what we are going to brief in this article. There are thousands of English words, and newer words are coined now and then.

Although it cannot be possible to review all existing words, let us explore some words for better vocabulary (that we commonly use) in alphabetical order and how to use them in sentences as nouns, adjectives, or verbs.

Vocabulary are the words that are used in sentences. The word vocabulary originates from the Latin word vocabulum. These vocabulary words put sense in the sentence and make the sentence meaningful. Some people use common or easy vocabulary words. But there are other difficult or complex words that can be used in place of easy words.

If you want to learn vocabulary then here are some tips- read as much as you can, read newspapers, journals, and articles. Learn a new word every day. Engage with people. Try to have conversations with them. Refer to the dictionary if you are not able to find the meaning of a particular word. Dictionary not just consist of word meanings, it also provide you the sentences so that you are able to learn how we can use a word in a sentence.

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You will see GRE vocabulary on test day in a variety of ways. Your verbal score is generated from 27 questions that are split up into two sections. The first section consists of 12 questions and the second section consists of 15 questions. You will have 18 minutes to complete the first section and 23 minutes for the second section, so be ready to tackle Sentence Equivalence, Text Completion, and Reading Comprehension questions.

Knowing how to decipher difficult vocabulary by using the context is extremely helpful in maximizing your GRE verbal score. Take the quiz below to test your understanding of some of the 52 top GRE vocabulary words, and then review the examples and definitions of each word at the bottom of the page.

For many people, the word vocabulary is primarily associated with the number of words that a person knows; one either has a large or a small vocabulary. But the word has many shades of meaning and is nicely representative of the nuanced and multi-hued nature of so much of the English lexicon.

When i tried to get word embeddings of a sentence using bio_clinical bert, for a sentence of 8 words i am getting 11 token ids(+start and end) because "embeddings" is an out of vocabulary word/token, that is being split into em, bed ,ding, s.

To my knowledge, mean aggregation is the most commonly used tool here, and in fact there is even scientific literature, empirically showing that it works well:Generalizing Word Embeddings using Bag of Subwords by Zhao, Mudgal and Liang. Formula 1 is describing exactly what you are proposing as well.

The one alternative that you could theoretically employ is something like a mean aggregate over the entire input, essentially making a "context prediction" over all words (potentially except "embeddings"), therefore emulating something similar to the [MASK]ing during training of the transformer models. But this is just a suggestion from me without any backup of scientific evidence that it works (for better or worse).

When i tried to get word embeddings of a sentence using bio_clinical bert, for a sentence of 8 words i am getting 11 token ids(+start and end) because "embeddings" is an out of vocabulary word/token, that is being split into em,bed,ding,s.

I'm not sure there is a need for aggregation, or in other words you may have a pipeline mismatch. BERT sentencepiece tokenization is specifically meant to be passed to some set downstream pipelines, with the aim of the sentencepiece thing being to be able to cater to OOV words. By aggregating the sentencepiece tokens, you might be doing away with the benefit of being able to cater to OOV in your later pipeline.

If you are looking for whole word vector tokens, and want to work with OOV words, I would recommend looking at FastText instead. This algorithm more or less uses subwords, and it will also build tokens for OOV words by pretty much aggregating the subword information for that OOV word during a custom training step. The benefit here is that the aggregation step need not be part of your pipeline, and you can use these new vectors in any downstream task (except, of course, the pipelines that accept BERT sentencepiece tokens)

We remember what is relevant to us. Making lists or index cards with random words is not usually an effective way to remember and use these words later. Word lists and index cards are great for revisiting vocabulary you have already learned, but to make a new word stick in your mind, try linking it with something meaningful to you. You will be more likely to remember a new word if it is used in a context you find interesting or are passionate about. For example, if you are a football fan, there are more chances you will remember the word 'unstoppable' in a sentence, such as 'Messi is unstoppable', rather than just as a single word or in a generic sentence, e.g. 'Some people are unstoppable'.

Tip: The British Council LearnEnglish website features tons of interactive videos, games and podcasts. No matter what topic interests you, you will always find something there. There are also discussion boards under activities, so you can share your ideas with other learners.

Tip: If you are into learning with video, TV and films, try FluentU. There are interactive captions, so if you tap on any word, you will see an image, definition and useful examples. You can also find other interesting resources featuring words in context. For example, this 'SpeakSmart' collection on Instagram has different scenes from popular television series giving examples of particular words and phrases in use. If you love reading, try reading short texts, such as cartoon strips. There are many comics available online, including those for language learners, like Grammarman, which you can also listen to while you read.

Learning is essentially an internal process. To learn a word, you need to get into the world of your inner voice. Try the following: listen to a word/phrase once, now listen to it inside your head, then say it inside your head, then say it aloud. Record yourself saying it and listen to the recording. Does it sound the way you heard it with your inner ear?

Try to create a funny phrase or story that will strengthen the connection between the word and its meaning (known as a mnemonic). I find this technique especially effective when I need to recall words that are hard to spell.

Repetition fixes new words in your memory. However, repeating them a hundred times over the course of one day will not be as effective as repeating them a few times over a period of several days or weeks (i.e., spaced repetition).

Before you look up the word in the dictionary, try to guess what it means. Look at its root, suffixes and prefixes. If you know a few languages, you will start recognising new words that share roots. Researching the origin of new words may help you retain new words better.

Tip: Instead of keeping these sentences to yourself, you can use them in writing games such as the Folding Story. This is an online version of the popular writing game where each player writes one line of a story and passes it on to another player to add to it. In the online version, each player gets just three minutes to write a line and scores points by the number of likes they receive for their lines.

Find further information about learning resources and opportunities on the British Council's LearnEnglish site or, if you're a teacher, join our community of English language teachers on Facebook.

The SAT has undergone a number of overhauls over the years that have made vocabulary a far less important part of the test. There are fewer vocabulary questions on the current SAT than there were on older versions of the exam, which include qustion types like analogies that focused solely on testing vocab knowledge.

Context clues make memorizing SAT vocab words less important on the current SAT than it was on the old SAT, back when you had to memorize dozens of obscure words and answer questions that dealt with isolated sentences (these were called Sentence Completion problems). This made vocab questions particularly hard since you were given minimal context with which to solve them.

The new digital SAT has one Reading and Writing section broken into four domains: Craft and Structure, Information and Ideas, Standard English Conventions, and Expression of Ideas. Only one domain, Craft and Structure, includes vocabulary as a tested skill.

According to College Board's description of this domain, "Students will use comprehension, vocabulary, analysis, synthesis, and reasoning skills and knowledge to understand and use high-utility words and phrases in context, evaluate texts rhetorically, and make connections between topically related texts."

There are approximately 13-15 questions total in this domain, which makes up about 28 percent of the Reading and Writing section of the SAT. But as you can see from the description, vocabulary is not tested in isolation, but in context. That means you won't see a vocabulary word and then be asked to choose the correct definition. Instead, you'll be tested on whether you can use context clues to interpret certain vocabulary words and understand the meaning of a phrase or passage.

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