In the deftask blog I described how it lets users search for tasks easily by using natural language date queries. It accomplishes this by using a natural language date and time parser I wrote a long time ago called Chronicity.

But how exactly does Chronicity work? In this post, we’ll dig into its innards and get a sense of the steps involved in writing it.

If you want to hack into Chronicity, or write your own NLP date parser, this might help.

Note: credit for Chronicity’s architecture goes to the Ruby library Chronic. It served both as an inspiration and as the implementation reference.

Broadly, Chronicity follows these steps to parse date and time strings:

Normalize text

We normalize the text before tokenizing it by doing the following:

Lower case the string Convert numeric words (like “one”, “ten”, “third”, etc.) to the corresponding numbers Replace all the common synonyms of a word or phrase so that tokenizing becomes simpler.

All of this is accomplished by the PRE-NORMALIZE function. To convert numeric words to numbers the NUMERIZE function is used. One caveat: do not immediately normalize the term “second” – it can either mean the ordinal number or the unit of time. So we wait until after tokenization (see pre-process tokens) to resolve this ambiguity.

CHRONICITY> ( pre-normalize "tomorrow at seven" ) "next day at 7" CHRONICITY> ( pre-normalize "20 days ago" ) "20 days past"

Tokenize

Next we assign a token to each word in the normalized text.

( defclass token () (( word :initarg :word :reader token-word ) ( tags :initarg :tags :initform nil :accessor token-tags ))) ( defun create-token ( word &rest tags ) ( make-instance 'token :word word :tags tags ))

As you can see, besides the word, a token also contains a list of tags. Each tag indicates a possible way to interpret the given word or number. Take the phrase “20 days ago”. The number 20 can be interpreted in many ways:

It might refer to the 20th day of the month

It might be the year 2020

Or maybe just the number 20 (which is what is actually meant in the given phrase)

It could also refer to the time 8 PM in 24-hour format (20:00 hours)

Remember, we are still in the tokenization phase so we don’t know which interpretation is correct. So we will assign all four tags to the token for this number.

Each tag is a subclass of the TAG class, which is defined as follows.

( defclass tag () (( type :initarg :type :reader tag-type ) ( now :initarg :now :accessor tag-now :initform nil ))) ( defun create-tag ( class type &key now ) ( make-instance class :type type :now now ))

The slot TYPE is a misnomer – it actually indicates the designated value of the token for this tag. For example, the TYPE for the year 2020 above will be the integer 2020. For the time 8 PM it will be an object denoting the time.

The slot NOW has the current timestamp. It is used by some tag classes like REPEATER for date-time computations (discussed later).

The various subclasses of TAG are:

SEPARATOR – Things like slash “/”, dash “-“, “in”, “at”, “on”, etc.

– Things like slash “/”, dash “-“, “in”, “at”, “on”, etc. ORDINAL – Numbers like 1st, 2nd, 3rd, etc.

– Numbers like 1st, 2nd, 3rd, etc. SCALAR – Simple numbers like 1, 5, 10, etc. It is further subclassed by SCALAR-DAY (1-31), SCALAR-MONTH (1-12) and SCALAR-YEAR . A token for any number will usually contain the SCALAR tag plus one or more of the subclassed tags as applicable.

– Simple numbers like 1, 5, 10, etc. It is further subclassed by (1-31), (1-12) and . A token for any number will usually contain the SCALAR tag plus one or more of the subclassed tags as applicable. POINTER – Indicates whether we are looking forwards (“hence”, “after”, “from”) or backwards (“ago”, “before”). These words are normalized to “future” and “past” before they are tagged.

– Indicates whether we are looking forwards (“hence”, “after”, “from”) or backwards (“ago”, “before”). These words are normalized to “future” and “past” before they are tagged. GRABBER – The terms “this”, “last” and “next” (as in this month or last month).

– The terms “this”, “last” and “next” (as in this month or last month). REPEATER – Most of the date and time terms are tagged using this class. This is described in more detail below.

There are a number of subclasses of REPEATER to indicate the numerous date and time terms. For example:

Unit names like “year”, “month”, “week”, “day”, etc., use the subclasses REPEATER-YEAR , REPEATER-MONTH , REPEATER-WEEK , REPEATER-DAY .

, , , . REPEATER-MONTH-NAME is used to indicate month names like “jan” or “january”.

is used to indicate month names like “jan” or “january”. REPEATER-DAY-NAME indicates day names like “monday”.

indicates day names like “monday”. REPEATER-TIME is used to indicate time strings like 20:00.

is used to indicate time strings like 20:00. Parts of the day like AM, PM, morning, evening use the subclass REPEATER-DAY-PORTION .

In addition, all the REPEATER subclasses need to implement a few methods that are needed for date-time computations.

R-NEXT – Given a repeater and a pointer i.e. :PAST or :FUTURE , returns a time span in the immediate past or future relative to the NOW slot. For example, assume the date in NOW is 31st December 2018. (r-next repeater :past) for a REPEATER-MONTH will return a time span starting 1st November 2018 and ending at 30th November. (r-next repeater :future) will return a span for all of January 2019. Similarly, for a REPEATER-DAY this would have returned 30th December for :PAST and 1st January for the :FUTURE pointer.

– Given a repeater and a pointer i.e. or , returns a time span in the immediate past or future relative to the slot. For example, assume the date in is 31st December 2018. R-THIS is similar to R-NEXT except it works in the current context. The width of the span also depends on whether direction of the pointer. (r-this repeater :past) for a REPEATER-DAY will return a span from the start of day until now. (r-this repeater :future) will return a span from now until the end of day. (r-this repeater :none) will return the whole day today.

is similar to except it works in the current context. The width of the span also depends on whether direction of the pointer. R-OFFSET – Given a span, a pointer and an amount, returns a new span offset from the given span. The offset is roughly the amount mulitplied by the width of the repeater.

Now we can put the whole tokenization and tagging piece together:

( defun tokenize ( text ) ( mapcar #' create-token ( cl-ppcre:split # ?r "\s+" text ))) ( defun tokenize-and-tag ( text ) ( let (( tokens ( tokenize text ))) ( loop for type in ( list 'repeater 'grabber 'pointer 'scalar 'ordinal 'separator ) do ( scan-tokens type tokens )) tokens ))

As you can see, computing the tags for each token is accomplished by the SCAN-TOKENS . This is a generic function specialized on the class name of the tag.

One of the methods implementing SCAN-TOKENS is shown below.

( defmethod scan-tokens (( tag ( eql 'grabber )) tokens ) ( let (( scan-map ' (( "last" :last ) ( "this" :this ) ( "next" :next )))) ( dolist ( token tokens tokens ) ( loop for ( regex value ) in scan-map when ( cl-ppcre:scan regex ( token-word token )) do ( tag ( create-tag 'grabber value ) token ))))) ( defmethod tag ( tag token ) ( push tag ( token-tags token )))

Going back to our original example, for the text “20 days ago”, these are the tags set for each token (after normalization).

Token Tags ----- ---- 20 [SCALAR-YEAR, SCALAR-DAY, SCALAR, REPEATER-TIME] days [REPEATER-DAY] past [POINTER]

Pre-process tokens

We are almost ready to run pattern matching to figure out the input date, but first, we need to resolve the ambiguity related to the term second that we faced during normalization. At that time, we did not convert it to the number 2 since it could refer to either the unit of time or the number.

Now with tokenization done, we resolve this ambiguity with a simple hack: if the term second is followed by a repeater (i.e. month, day, year, january, etc.), we assume that it is the ordinal number 2nd and not the unit of time. See PRE-PROCESS-TOKENS for more details.

Pattern matching

The last piece of the puzzle is pattern matching. Armed with tokens and their corresponding tags, we define several date and time patterns that we know of and try to match them to their input tokens.

First we name a few pattern classes – each pattern we define belongs to one of these classes.

DATE – patterns that match an absolute date and time e.g. “1st January”, “January 1 at 2 PM”, etc.

– patterns that match an absolute date and time e.g. “1st January”, “January 1 at 2 PM”, etc. ANCHOR – patterns that typically involve a grabber e.g. “yesterday”, “tuesday” “last week”, etc.

– patterns that typically involve a grabber e.g. “yesterday”, “tuesday” “last week”, etc. ARROW – patterns like “2 days from now”, “3 weeks ago”, etc.

– patterns like “2 days from now”, “3 weeks ago”, etc. NARROW – patterns like “1st day this month”, “3rd wednesday in 2007”, etc.

– patterns like “1st day this month”, “3rd wednesday in 2007”, etc. TIME – simple time patterns like “2 PM”, “14:30”, etc.

A pattern, at its simplest, is just a list of tag classes. A list of input tokens successfully matches a pattern if, for every token, at least one of its tags is an instance of the tag class mentioned at the corresponding position in the pattern. For example, the text “20 days ago” had these tags:

Token Tags ----- ---- 20 [SCALAR-YEAR, SCALAR-DAY, SCALAR, REPEATER-TIME] days [REPEATER-DAY] past [POINTER]

It will match any of these patterns:

( scalar repeater pointer ) ( scalar repeater-day pointer ) (( ? scalar ) repeater pointer )

The last example shows a pattern with an optional tag – (? scalar) . It will match tokens with or without the scalar e.g. both “20 days ago” and “week ago” will match.

Our pattern matching engine also allows us to match an entire pattern class. For example,

( repeater-month-name scalar-day ( ? separator-at ) ( ? p time ))

(? p time) here means that any pattern that belongs to the TIME pattern class can match. So all of “January 1 at 12:30”, “January 1 at 2 PM” and “January 1 at 6 in the evening” will match without us needing to duplicate all the time patterns.

Note: There’s one limitation – a pattern class can only be specified at the end of a pattern in Chronicity. So a pattern like (repeater (p time) pointer) won’t work. This will be fixed in the future.

Each pattern has a handler function that decides how to convert the matching tokens to a date span.

A pattern and its handler function are defined using the DEFINE-HANDLER macro. It assigns one or more patterns to a pattern class, and if either of these patterns match, the function body is run. Its general form is:

( define-handler ( pattern-class ) ( tokens-var ) ( pattern1 pattern2 ... ) ... body ... )

An example handler is shown below.

( define-handler ( date ) ( tokens ) (( repeater-month-name scalar-year )) ( let* (( month-name ( token-tag-type 'repeater-month-name ( first tokens ))) ( month ( month-index month-name )) ( year ( token-tag-type 'scalar-year ( second tokens ))) ( start ( make-date year month ))) ( make-span start ( datetime-incr start :month ))))

Most handler functions will use make use of the the repeater methods R-NEXT , R-THIS and R-OFFSET that we described above.

Chronicity implements this pattern matching logic in the TOKENS-TO-SPAN function. All the patterns and their handler functions are defined inside handler-defs.lisp. Patterns defined earlier in the file get precedence over those defined later. If you add, remove or modify a handler, you should reload the whole file rather than just evaluating that handler’s definition.

Returning the result

Finally, we put everything together.

( defun parse ( text &key ( guess t )) ( let (( tokens ( tokenize-and-tag ( pre-normalize text )))) ( pre-process-tokens tokens ) ( values ( guess-span ( tokens-to-span tokens ) guess ) tokens )))

By default PARSE will return a timestamp instead of a time span. This depends on the value passed to the :GUESS keyword – see the GUESS-SPAN function to see how it is interpreted. If you want to return a time span send NIL instead.

The second value that this function returns is the list of tokens alongwith all its tags. This is useful for debugging Chronicity results in the REPL.

CHRONICITY> ( parse "20 days ago" ) @2018-12-12T12:01:53.758578+05:30 ( # <TOKEN 20 [SCALAR-YEAR, SCALAR-DAY, SCALAR, REPEATER-TIME] {1007639243}> # <TOKEN days [REPEATER-DAY] {10076AF5D3}> # <TOKEN past [POINTER] {1007553443}> ) CHRONICITY> ( parse "20 days ago" :guess nil ) # <SPAN 2018-12-12T00:00:00.000000+05:30..2018-12-13T00:00:00.000000+05:30> ( # <TOKEN 20 [SCALAR-YEAR, SCALAR-DAY, SCALAR, REPEATER-TIME] {1001B78BC3}> # <TOKEN days [REPEATER-DAY] {1001B78C03}> # <TOKEN past [POINTER] {1001B78C43}> )

The actual PARSE function has a few more bells and whistles than the one defined here: