Parse example sentences

"Parse" Example Sentences

1. The parser analyzes sentences and breaks them down into grammatical parts like verbs, nouns and adjectives.
2. We had to parse the difficult sentence to understand its meaning.
3. The computer program carefully parsed the transcript to identify parts of speech.
4. Her new machine could accurately parse over 200,000 sentences per minute.
5. The grammar book taught me how to properly parse simple sentences.
6. The students had to parse the long passage sentence by sentence.
7. He parsed the complicated string of phrases into a more manageable set of clauses.
8. The developers used complex algorithms to parse the unstructured data.
9. The linguists parsed the ancient text to analyze its grammar and syntax.
10. The computer program parsed the email message for spam words.
11. Speech recognition software parses spoken words into text.
12. The part of speech tagger parsed the words into grammatical categories.
13. The grammar tool parsed the new words correctly based on their suffixes.
14. They parsed the big paragraph into individual sentences for analysis.
15. The database parsed search queries to determine relevant results.
16. The software parsed and filtered the vast amount of data.
17. Numerous tools and APIs exist to parse both XML and JSON files.
18. Scholars carefully parsed ancient texts to better understand their meaning.
19. Natural language parsers translate text into meaningful data structures.
20. The bot parsed each question for keywords before giving a response.
21. I had to parse each complex sentence slowly to grasp its structure.
22. We parsed the long passage looking for specific themes and examples.
23. They parsed the data into categories based on timestamps and locations.
24. The natural language processing system parsed the sentences for entities and relations.
25. The machine learning model parsed user requests for actionable parameters.
26. The translation program parsed the foreign text before rendering it into English.
27. We used an online parser to check the grammar of our writing.
28. The legal team carefully parsed the contracts for ambiguities and errors.
29. Complex parsers are needed to handle complex grammar and structure.
30. The system parsed the noisy data for meaningful patterns and trends.
31. We parsed the document into headings, subheadings and main body text.
32. The program parsed the input from various sources into a uniform format.
33. Parsers identify dependencies between elements in a sequence.
34. The syntactical parser broke down the grammatical structure of the sentence.
35. The linguistic model parsed phoneme sequences into possible word options.
36. The library parsed XML into regular Python lists and dictionaries.
37. We parsed the long sentence to identify its subject, verb and object.
38. The semantic parser generated meaning representations for the utterances.
39. The components were parsed into smaller modules for easier maintenance.
40. The syntax trees were generated by parsing the sentences.
41. The library parsed JSON data into native Python types.
42. The library parsed the messy spreadsheet data into clean arrays and dictionaries.
43. The system parsed conversational text into its functional components.
44. We parsed the document for relevant information about particular topics.
45. The script parsed log data into structured events for analysis.
46. The chart parsed data in different ways to expose hidden patterns.
47. The tool parsed the unstructured text data to extract named entities.
48. The search engine algorithm parsed queries to determine matches.
49. The compiler parsed the program into a syntax tree before code generation.
50. The decoder parsed the bitstream into individual signals and symbols.
51. The registrar parsed the student transcripts for credit transfers.
52. The professor parsed each student's essay for grammatical mistakes.
53. The recipe parser broke down cooking instructions into executable steps.
54. Parse trees reveal the syntactic structure of sentences and phrases.
55. The sentence parser attempted to determine the most likely structure.
56. The part of speech parser identified grammatical classes of each word.
57. The expression parser correctly interpreted the complex mathematical formula.
58. The story parser broke down the plot into its major events and twists.
59. The data parser standardized the input into a uniform output format.
60. We parsed the difficult text passage for its deeper meaning and implications.

Common Phrases

1. The parser attempted to parse the erroneous syntax.
2. The compiler threw an error when it attempted to parse the malformed code.
3. The natural language processing algorithm parses text to identify parts of speech.
4. The speech recognition software parses audio input to determine the spoken words.
5. The data mining program parses the log files to extract relevant information.
6. The machine reads the text and parses it into grammatical units.
7. The web crawler parses HTML pages to index their content.
8. The computational model parses text input to generate a semantic representation.
9. She parsed the legal document carefully to check for any errors or omissions.
10. They parsed the coordinates from the GPS data.
11. The security software parses network packets for any malicious content.
12. The mapping software parses location data from the geotag information.
13. The program parses the input string according to the specified grammar rules.
14. The linguistics software parses the sentence into its constituent phrases.
15. The sentence parser breaks the sentence down into its basic elements.
16. The parser produces a parse tree that represents the syntactic structure of the sentence.
17. The URL parser extracts relevant components from the web address.
18. She parsed the instructions carefully to find any ambiguities.
19. The syntax parser checks that the program code follows the language grammar.
20. The JSON parser converts the JSON string into a native object.
21. The data extractor parses the input data and populates the database.
22. The information retrieval system parsed the corpus of documents.
23. The database parses the XML data and stores it in the designated tables.
24. The regular expression parser parses the input string according to the specified regex pattern.
25. The markup language parser parses the XML data into a DOM tree.
26. The predictive text application parses the grammar rules to identify word combinations.
27. They parsed the complex contract to check for any loopholes.
28. The program parses the string of characters into individual words.
29. The CSV parser splits comma-separated records into rows and columns.
30. She parsed the official report carefully to summarize the key findings.
31. The equation parser interprets mathematical expressions.
32. The argument parser extracts command line arguments and options.
33. The portfolio parser extracts stock data from financial statements.
34. The XML parser converts XML data into objects that can be manipulated programmatically.
35. An optical character recognition engine parses scanned text into individual characters.
36. The rules engine parses if-then statements to generate inferences.
37. The language parser deconstructs language input into meaningful parts.
38. The text parser breaks the text down into constituent parts.
39. The syntax parser checks sentences for grammatical correctness.
40. The mathematical expression parser converts equations into an expression tree.
41. The query parser converts a query string into a structured query.
42. The chemical formula parser breaks down chemical formulae into ions and molecules.
43. The markup parser interprets tags and determines the document structure.
44. The statistical parser computes the most likely parse tree for a given sentence.
45. The semantic parser maps natural language to a formal meaning representation.
46. The phrase parser decomposes a phrase into its head and modifiers.
47. The dependency parser identifies grammatical relationships between words.
48. The evaluator parses and interprets code on the fly.
49. The sentiment analysis model parses text to determine positive and negative sentiment.
50. The linguistic parser segments text into syntactic categories.
51. The probabilistic parser outputs the most likely syntax trees.
52. The recursive descent parser builds a parse tree by recursive calls.
53. The predictive parser anticipates future input based on the current parse.
54. The top-down parser builds the parse tree from the root node down.
55. The bottom-up parser builds the parse tree from the leaf nodes up.
56. The parser interprets and evaluates the programming syntax.
57. The parser converts unstructured text into a structured format.
58. The script parser interprets script commands and executes them.
59. The address parser extracts components such as name, street, city, and zip code.
60. The compiler parser analyzes the source code and generates a parse tree.