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Compromise API Reference

Every method returns a new View (a sub-selection of the document) unless noted, so calls chain: nlp(text).match('#Verb').toPastTense().text(). Methods are grouped by what they do.

Method availability depends on the build tier: compromise/one (tokenize), compromise/two (+tags & contractions), and the default compromise / compromise/three (+ all selections below).

Core methods

(available on every View)

• .case [getter] — preserve the case of the original, ignoring the case of the replacement
• .possessives [getter] — preserve whether the original was a possessive
• .tags [getter] — preserve all of the tags of the original, regardless of the tags of the replacement

Utils

• .found [getter] — is this document empty?
• .docs [getter] — get a list of term objects for this view
• .document [getter] — get the full parsed text
• .pointer [getter] — the indexes for the current view
• .fullPointer [getter] — explicit indexes for the current view
• .methods [getter] — access internal library methods
• .model [getter] — access internal library data
• .hooks [getter] — which compute methods run by default
• .isView [getter] — helper for detecting a compromise object
• .length [getter] — count the # of characters of each match
• .update(pointer) — create a new view, from this document
• .toView(pointer) — turn a Verb or Noun view into a normal one
• .fromText(text) — create a new document
• .termList() — .docs [alias]
• .compute(method) — run a named operation on the document
• .clone(shallow?) — deep-copy the document, so that no references remain

Loops

• .forEach(fn) — run a function on each phrase, as an individual document
• .map(fn, emptyResult?) — run each phrase through a function, and create a new document
• .filter(fn) — return only the phrases that return true
• .find(fn) — return a document with only the first phrase that matches
• .some(fn) — return true or false if there is one matching phrase
• .random(n?) — sample a subset of the results

Accessors

• .terms(n?) — split-up results by each individual term
• .groups(name?) — grab a specific named capture group
• .eq(n) — use only the nth result
• .first(n?) — use only the first result(s)
• .last(n?) — use only the last result(s)
• .firstTerms() — get the first word in each match
• .lastTerms() — get the end word in each match
• .slice(start, end?) — grab a subset of the results
• .all() — return the whole original document ('zoom out')
• .fullSentences() — return the full original sentence for each match
• .none() — return an empty view
• .isDoc(view?) — are these two views of the same document?
• .wordCount() — count the # of terms in each match

Match

• .match(match, group?, options?) — return matching patterns in this doc
• .matchOne(match, group?, options?) — return only the first match
• .has(match, group?, options?) — Return a boolean if this match exists
• .if(match, group?, options?) — return each current phrase, only if it contains this match
• .ifNo(match, group?, options?) — Filter-out any current phrases that have this match
• .before(match, group?, options?) — return the terms before each match
• .after(match, group?, options?) — return the terms after each match
• .lookBehind(match, group?, options?) — alias of .before()
• .lookBefore(match, group?, options?) — alias of .before()
• .lookAhead(match, group?, options?) — alias of .after()
• .lookAfter(match, group?, options?) — alias of .after()
• .growLeft(match, group?, options?) — add any immediately-preceding matches to the view
• .growRight(match, group?, options?) — add any immediately-following matches to the view
• .grow(match, group?, options?) — expand the view with any left-or-right matches
• .sweep(match, opts?) — apply a sequence of match objects to the document
• .splitOn(match?, group?) — .split() [alias]
• .splitBefore(match?, group?) — separate everything after the match as a new phrase
• .splitAfter(match?, group?) — separate everything before the word, as a new phrase
• .split(match?, group?) — splitAfter() alias

Case

• .toLowerCase() — turn every letter of every term to lower-cse
• .toUpperCase() — turn every letter of every term to upper case
• .toTitleCase() — upper-case the first letter of each term
• .toCamelCase() — remove whitespace and title-case each term

Insert

• .concat(input) — add these new things to the end
• .insertBefore(input) — add these words before each match
• .prepend(input) — insertBefore() alias
• .insertAfter(text) — add these words after each match
• .append(text) — insertAfter() alias
• .insert(text) — insertAfter() alias
• .remove(match) — fully remove these terms from the document
• .delete(match) — alias for .remove()
• .replace(from, to?, keep?) — search and replace match with new content
• .replaceWith(to, keep?) — substitute-in new content
• .unique() — remove any duplicate matches
• .reverse() — reverse the order of the matches, but not the words
• .sort(method?) — re-arrange the order of the matches (in place)
• .normalize(options?) — cleanup various aspects of the words

Whitespace

• .pre(str?, concat?) — add this punctuation or whitespace before each match
• .post(str?, concat?) — add this punctuation or whitespace after each match
• .trim() — remove start and end whitespace
• .hyphenate() — connect words with hyphen, and remove whitespace
• .dehyphenate() — remove hyphens between words, and set whitespace
• .deHyphenate() — alias for .dehyphenate()
• .toQuotations(start?, end?) — add quotation marks around selections
• .toQuotation(start?, end?) — alias for toQuotations()
• .toParentheses(start?, end?) — add parentheses around selections

Output

• .text(options?) — return the document as text
• .json(options?) — pull out desired metadata from the document
• .debug() — pretty-print the current document and its tags
• .out(format?) — some named output formats
• .html(toHighlight) — produce an html string
• .wrap(matches) — produce an html string

Pointers

• .union(match) — return all matches without duplicates
• .and(match) — .union() alias
• .intersection(match) — return only duplicate matches
• .not(match, options?) — return all results except for this
• .difference(match, options?) — .not() alias
• .complement(match) — get everything that is not a match
• .settle(match) — remove overlaps in matches

Tag

• .tag(tag, reason?) — Give all terms the given tag
• .tagSafe(tag, reason?) — Only apply tag to terms if it is consistent with current tags
• .unTag(tag, reason?) — Remove this term from the given terms
• .canBe(tag) — return only the terms that can be this tag

Cache

• .cache(options?) — freeze the current state of the document, for speed-purposes
• .uncache(options?) — un-freezes the current state of the document, so it may be transformed
• .freeze() — prevent current tags from being removed
• .unfreeze() — allow current tags to be changed [default]
• .lookup(trie, opts?) — quick find for an array of string matches
• .autoFill() — assume any type-ahead prefixes
• .contractions(n?) — return any multi-word terms, like "didn't"
• .contract() — contract words that can combine, like "did not"
• .confidence() — Average measure of tag confidence
• .swap(fromLemma, toLemma, guardTag?) — smart-replace root forms
• .expand() — turn "i've" into "i have"

Selections (compromise/three)

These return specialised sub-views with extra methods. e.g. doc.verbs().toPastTense().

Selection methods on any View

• .clauses(n?) — split-up results into multi-term phrases
• .chunks() — split-up noun-phrase and verb-phrases
• .normalize(options?) — clean-up the document, in various ways
• .redact(opts?, blockStr?, keepTags?) — remove any people, places, and organizations
• .hyphenated(n?) — return all terms connected with a hyphen or dash like 'wash-out'
• .hashTags(n?) — return terms like '#nlp'
• .emails(n?) — return terms like '[email protected]'
• .emoji(n?) — return terms like 💋
• .emoticons(n?) — return terms like :)
• .atMentions(n?) — return terms like '@nlp_compromise'
• .urls(n?) — return terms like 'compromise.cool'
• .pronouns(n?) — return terms like 'he'
• .conjunctions(n?) — return terms like 'but'
• .prepositions(n?) — return terms like 'of'
• .honorifics(n?) — return terms like 'Dr.'
• .abbreviations(n?) — return terms like 'st.'
• .phoneNumbers(n?) — return terms like '(939) 555-0113'
• .addresses(n?) — return terms like '23 Park Avenue'
• .acronyms(n?) — return terms like 'FBI'
• .parentheses(n?) — return anything inside (parentheses)
• .possessives(n?) — return terms like "Spencer's"
• .quotations(n?) — return any terms inside 'quotation marks'
• .slashes(n?) — return any slashed terms like 'love/hate'
• .adjectives(n?) — return words like "clean"
• .adverbs(n?) — return words like "quickly"
• .nouns(n?, opts?) — return noun phrases in the view
• .numbers(n?, opts?) — return any numbers in the view
• .percentages(n?, opts?) — return any percentages in the view
• .money(n?, opts?) — return any money in the view
• .fractions(n?, opts?) — return any fractions in the view
• .sentences(n?, opts?) — return full sentences in the view
• .questions(n?, opts?) — find full sentences of any questions in the view
• .verbs(n?) — return any subsequent terms tagged as a Verb
• .people(n?) — return person names like 'John A. Smith'
• .places(n?) — return location names like 'Paris, France'
• .organizations(n?) — return companies and org names like 'Google Inc.'
• .topics(n?) — return people, places, and organizations

.nouns() →

• .parse(n?) — grab the parsed noun-phrase
• .isPlural() — return only plural nouns
• .adjectives() — get any adjectives describing this noun
• .toPlural(setArticle?) — 'football captain' → 'football captains'
• .toSingular(setArticle?) — 'turnovers' → 'turnover'

.numbers() →

• .parse(n?) — grab the parsed number
• .get(n?) — grab the parsed number
• .isOrdinal() — return only ordinal numbers
• .isCardinal() — return only cardinal numbers
• .isUnit(units) — return only numbers with the given unit(s), like 'km'
• .toNumber() — convert number to 5 or 5th
• .toLocaleString() — add commas, or nicer formatting for numbers
• .toText() — convert number to five or fifth
• .toCardinal() — convert number to five or 5
• .toOrdinal() — convert number to fifth or 5th
• .isEqual() — return numbers with this value
• .greaterThan(min) — return numbers bigger than n
• .lessThan(max) — return numbers smaller than n
• .between(min, max) — return numbers between min and max
• .set(n) — set number to n
• .add(n) — increase number by n
• .subtract(n) — decrease number by n
• .increment() — increase number by 1
• .decrement() — decrease number by 1

.fractions() →

• .parse(n?) — grab the parsed number
• .get(n?) — grab the parsed number
• .toDecimal() — convert '1/4' to 0.25
• .toFraction() — convert 'one fourth' to 1/4
• .toOrdinal() — convert '1/4' to '1/4th'
• .toCardinal() — convert '1/4th' to '1/4'
• .toPercentage() — convert '1/4' to 25%

.sentences() →

• .parse(n?) — grab the parsed sentence
• .toPastTense() — 'will go' → 'went'
• .toPresentTense() — 'walked' → 'walks'
• .toFutureTense() — 'walked' → 'will walk'
• .toInfinitive() — 'walks' → 'walk'
• .toNegative() — 'he is cool' → 'he is not cool'
• .toPositive() — 'he isn't cool' -> 'he is cool'
• .isQuestion() — keep only questions
• .isExclamation() — keep only sentences with an exclamation-mark
• .isStatement() — remove questions, and exclamations

.people() →

• .parse() — get first/last/middle names

.verbs() →

• .parse(n?) — grab the parsed verb-phrase
• .subjects() — grab what [doing] the verb
• .adverbs() — return the adverbs describing this verb
• .isSingular() — return only singular nouns
• .isPlural() — return only plural nouns
• .isImperative() — only verbs that are instructions
• .toInfinitive() — 'walks' → 'walk'
• .toPresentTense() — 'walked' → 'walks'
• .toPastTense() — 'will go' → 'went'
• .toFutureTense() — 'walked' → 'will walk'
• .toGerund() — 'walks' → 'walking'
• .toPastParticiple() — 'walks' → 'has walked'
• .conjugate() — return all forms of these verbs
• .isNegative() — return verbs with 'not'
• .isPositive() — only verbs without 'not'
• .toPositive() — "didn't study" → 'studied'
• .toNegative() — 'went' → 'did not go'

.acronyms() →

• .strip() — 'F.B.I.' -> 'FBI'
• .addPeriods() — 'FBI' -> 'F.B.I.'

.parentheses() →

• .strip() — remove ( and ) punctuation

.possessives() →

• .strip() — "spencer's" -> "spencer"

.quotations() →

• .strip() — remove leading and trailing quotation marks

.slashes() →

• .split() — turn 'love/hate' into 'love hate'

.adjectives() →

• .adverbs() — get the words describing this adjective
• .conjugate() — return all forms of these
• .toComparative(n?) — 'quick' -> 'quicker'
• .toSuperlative(n?) — 'quick' -> 'quickest'
• .toAdverb(n?) — 'quick' -> 'quickly'
• .toNoun(n?) — 'quick' -> 'quickness'

Constructor methods (nlp.*)

(called on the imported nlp object, not a View)

• nlp.tokenize(text, lexicon?) — interpret text without tagging
• nlp.lazy(text, match?) — scan through text with minimal analysis
• nlp.plugin(plugin) — mix in a compromise-plugin
• nlp.extend(plugin) — mix-in a compromise plugin
• nlp.parseMatch(match, opts?) — turn a match-string into json
• nlp.world() — grab library internals
• nlp.model() — grab library metadata
• nlp.methods() — grab exposed library methods
• nlp.hooks() — which compute functions run automatically
• nlp.verbose(toLog?) — log our decision-making for debugging
• nlp.version — current semver version of the library
• nlp.addTags(tags) — connect new tags to tagset graph
• nlp.addWords(words, isFrozen?) — add new words to internal lexicon
• nlp.buildTrie(words) — turn a list of words into a searchable graph
• nlp.buildNet(matches) — compile a set of match objects to a more optimized form
• nlp.typeahead(words) — add words to the autoFill dictionary