The purpose of tidylex is to provide a collaborative, open-source, cross-platform tool for tidying dictionary data stored as Toolbox-style backslash-coded data (a broad convention for serializing lexicographic data in a human-readable and -editable manner). This format is commonly used in the description of under-documented languages, many of which are also highly endangered.
The example below shows a toy French-to-English dictionary with 3
entries rouge, bonjour, and parler with various lexicographic
information about these 3 entries (lx: lexeme, ps: part of speech,
de: definition, xv: example, vernacular in source language, xe:
translation, English). Tidylex makes it easy to make assertions of how
these entries should be structured, test whether or not they are
well-structured (examples provided below), and, most
importantly, communicate the results of these tests with relevant
parties.
\lx rouge \ps adjective \de red \xv La chaise est rouge \xe The chair is red \lx bonjour \de hello \ps exclamation \lx parler \ps verb \de speak \xv Parlez-vous français?
Owing to the dictionary data having been hand-edited over many years, often by multiple contributors, there is often a lot of structural inconsistency in these plain-text files. Given the structural variation, the knowledge about these languages are effectively ‘locked up’ in terms of machine-processability. Tidylex provides a set of functions to iteratively work towards a well-structured, or ‘tidy’, lexicon, and maintain the tidiness of the lexicon when used within a Continuous Testing setting (e.g. with Travis CI, or GitLab pipelines).
You can install tidylex from github with:
# install.packages("devtools")
devtools::install_github("CoEDL/tidylex")As there is project-to-project variation in coding convention (for
\lx, some others use \me for main entry, or ‘.’ in place of
backslashes, e.g. .i bonjour), the read_lexicon function provides a
quick way to specify a regular expression to parse each line in the
dictionary into its various components.
library(tidylex)
# The path to the 'rouge, bonjour, parler' dictionary shown in the example above
lexicon_file <- system.file("extdata", "error-french.txt", package = "tidylex")
lexicon_df <- read_lexicon(
file = lexicon_file,
regex = "\\\\?([a-z]*)\\s?(.*)", # Note two capture groups, in parentheses
into = c("code", "value") # Captured data placed, respectively, in 'code' and 'value' columns
)
lexicon_df
#> # A tibble: 14 x 4
#> line data code value
#> <int> <chr> <chr> <chr>
#> 1 1 "\\lx rouge" lx rouge
#> 2 2 "\\ps adjective" ps adjective
#> 3 3 "\\de red" de red
#> 4 4 "\\xv La chaise est rouge" xv La chaise est rouge
#> 5 5 "\\xe The chair is red" xe The chair is red
#> 6 6 "" "" ""
#> 7 7 "\\lx bonjour" lx bonjour
#> 8 8 "\\de hello" de hello
#> 9 9 "\\ps exclamation" ps exclamation
#> 10 10 "" "" ""
#> 11 11 "\\lx parler" lx parler
#> 12 12 "\\ps verb" ps verb
#> 13 13 "\\de speak" de speak
#> 14 14 "\\xv Parlez-vous français?" xv Parlez-vous français?A common pre-processing routine that must be done is to group the lines
into various subgroups, e.g. within some given entry, or within some
given sense of the entry, etc. We can easily do this with the
add_group_col function.
grouped_lxdf <-
lexicon_df %>%
add_group_col(
name = lx_group, # Name of the new grouping column
where = code == "lx", # When to fill with a value, i.e. when *not* to inherit value
value = paste0(line, ": ", value) # What the value should be when above condition is true
)
grouped_lxdf
#> # A tibble: 14 x 5
#> # Groups: lx_group [3]
#> line data code value lx_group
#> <int> <chr> <chr> <chr> <chr>
#> 1 1 "\\lx rouge" lx rouge 1: rouge
#> 2 2 "\\ps adjective" ps adjective 1: rouge
#> 3 3 "\\de red" de red 1: rouge
#> 4 4 "\\xv La chaise est rouge" xv La chaise est rouge 1: rouge
#> 5 5 "\\xe The chair is red" xe The chair is red 1: rouge
#> 6 6 "" "" "" 1: rouge
#> 7 7 "\\lx bonjour" lx bonjour 7: bonj…
#> 8 8 "\\de hello" de hello 7: bonj…
#> 9 9 "\\ps exclamation" ps exclamation 7: bonj…
#> 10 10 "" "" "" 7: bonj…
#> 11 11 "\\lx parler" lx parler 11: par…
#> 12 12 "\\ps verb" ps verb 11: par…
#> 13 13 "\\de speak" de speak 11: par…
#> 14 14 "\\xv Parlez-vous français?" xv Parlez-vous français? 11: par…Tidylex lets you define and use basic Nearley grammars within R to test for well-formedness of strings [1]. We begin by forming a set of strings to test. In the example below, we simple concatenate all the codes within the 3 entry groups into a single string:
entry_strs <-
grouped_lxdf %>%
summarise(code_sequence = paste0(code, collapse = " "))
entry_strs
#> # A tibble: 3 x 2
#> lx_group code_sequence
#> <chr> <chr>
#> 1 1: rouge "lx ps de xv xe "
#> 2 11: parler lx ps de xv
#> 3 7: bonjour "lx de ps "For such sequences above, we can define a context-free grammar
(equivalent to phrase structure rules) within the Nearley notation below
(:?, :+ are quantifiers indicating, respectively, ‘zero or one’ and
‘one or more’ of the preceding entity). We use the compile_grammar
function to generate code that can be used to test strings as to whether
or not they are well-formed.
entry_parser <- compile_grammar('
headword -> "lx" _ "ps" _ "de" _ examples:?
examples -> ("xv" _ "xe" _):+
_ -> " "
')
parsed_entries <-
entry_strs %>%
rowwise() %>%
mutate(parsed_sequence = entry_parser(code_sequence, stop_on_error = FALSE))
# Remove successful parse trees (which are lists, and retain only error message strings)
parsed_entries %>%
filter(!is.list(parsed_sequence)) %>%
mutate(parsed_sequence = unlist(parsed_sequence))
#> Source: local data frame [2 x 3]
#> Groups: <by row>
#>
#> # A tibble: 2 x 3
#> lx_group code_sequence parsed_sequence
#> <chr> <chr> <chr>
#> 1 11: parler lx ps de xv Error: Parse incomplete, expecting more text a…
#> 2 7: bonjour "lx de ps " "Error: invalid syntax at line 1 col 4:\n\n l…As we can see from the errors, the parler entry is missing an
obligatory xe (English translation) for the xv code, while the
bonjour entry is invalid because the de and ps codes have been
reversed (relative to the order required by the grammar above headword -> "lx" _ "ps" _ "de" ...).
Footnotes
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