PHPCLANCHILDES with regular expressions

Regular expression

Press Enter to search, Shift+Enter for a new line.

More conditions (like a second grep)

The utterance must also match

…and must not match

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Speakers

Context

Ignore case Whole words

Scope One transcript: french/unkeler_pie21.cha change

Searching only french/unkeler_pie21.cha. Search all transcripts instead

5 matches in 5 utterances

13.33 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (100 utterances, 375 words searched).

Concordance Utterances Distribution Matched forms

on va mouiller l'éponge d'abord ? MOT · french/unkeler_pie21.cha, line 260 · Pierre 2;01
viens on y va tous les deux . MOT · french/unkeler_pie21.cha, line 265 · Pierre 2;01
qu'est-ce qu'on va faire ? MOT · french/unkeler_pie21.cha, line 271 · Pierre 2;01
on va mouiller quoi ? MOT · french/unkeler_pie21.cha, line 282 · Pierre 2;01
mais attends , attends on va effacer d'abord ! MOT · french/unkeler_pie21.cha, line 362 · Pierre 2;01

One dot per transcript: matches per 1,000 words of everyone but CHI. Dots of the same child are joined.

per 1,000 words

051015

2;002;012;022;03

Age of the child (years;months)

Matches per 1,000 words, all transcripts of each child together, highest first.

All transcripts as a table

Transcript	Child	Age	Words	Utterances matched	Matches	Per 1,000 words
french/unkeler_pie21.cha	Pierre	2;1.20	375	5	5	13.33

1 different forms (lowercased). Useful to see what a pattern really catches: unexpected forms here usually mean the pattern is too broad.