PHPCLANCHILDES with regular expressions

5 matches in 5 utterances

2.47 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (502 utterances, 2,022 words searched).

  1. she's gonna have her lunch . COL · eng_USA_Brown/eve11.cha, line 1432 · Eve 1;11
  2. what are you gonna do today ? COL · eng_USA_Brown/eve11.cha, line 1670 · Eve 1;11
  3. well Sarah's gonna have some milk . MOT · eng_USA_Brown/eve11.cha, line 1835 · Eve 1;11
  4. she's gonna have some milk first # then she'll have a nap . MOT · eng_USA_Brown/eve11.cha, line 1840 · Eve 1;11
  5. what are you gonna fix it with # Eve ? COL · eng_USA_Brown/eve11.cha, line 2125 · Eve 1;11
  1. eng_USA_Brown/eve11.cha, line 1432 · Eve, 1;11.
    CHIlook it Sarah .
    CHISarah .
    COL*COL: she's gonna have her lunch .
    CHIshe gonna have you lunch .
    CHIshe goin(g) in my high+chair .
  2. eng_USA_Brown/eve11.cha, line 1670 · Eve, 1;11.
    CHIyou write with this .
    COLokay # I'll write with this .
    COL*COL: what are you gonna do today ?
    CHIFraser # the dolls not in you briefcase .
    COLthe dolls +...
  3. eng_USA_Brown/eve11.cha, line 1835 · Eve, 1;11.
    MOTI did .
    CHISarah take a nap .
    MOT*MOT: well Sarah's gonna have some milk .
    MOTshe's gonna have some milk first # then she'll have a nap .
    CHII write yours .
  4. eng_USA_Brown/eve11.cha, line 1840 · Eve, 1;11.
    CHISarah take a nap .
    MOTwell Sarah's gonna have some milk .
    MOT*MOT: she's gonna have some milk first # then she'll have a nap .
    CHII write yours .
    CHIwith my pencil .
  5. eng_USA_Brown/eve11.cha, line 2125 · Eve, 1;11.
    MOTfix it with the scissors ?
    MOTwell it'll be easier .
    COL*COL: what are you gonna fix it with # Eve ?
    CHIPapa .
    COLyeah # what's Papa going to use ?

Matches by age

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

Matches by child

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

  1. Eve eng_USA_Brown2.47
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/eve11.chaEve 1;11.2,022552.47

What the pattern matched

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

  1. gonna5 · 100.0%