PHPCLANCHILDES with regular expressions

7 matches in 6 utterances

16.39 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (88 utterances, 427 words searched).

  1. should we put some little people in them ? MOT · eng_USA_Bates/nan28.cha, line 93 · Nan 2;04
  2. should we keep putting people in them ?%mor: v:aux|should pro|we v|keep part… MOT · eng_USA_Bates/nan28.cha, line 110 · Nan 2;04
  3. should we keep putting people in them ?%mor: v:aux|should pro|we v|keep part|put-PROG n|person&PL prep|in pro|them ? MOT · eng_USA_Bates/nan28.cha, line 110 · Nan 2;04
  4. where should we put the rooster ? MOT · eng_USA_Bates/nan28.cha, line 188 · Nan 2;04
  5. should +... MOT · eng_USA_Bates/nan28.cha, line 424 · Nan 2;04
  6. where should we put the people ? MOT · eng_USA_Bates/nan28.cha, line 427 · Nan 2;04
  7. should I take the yellow one off or you want to put that on top ? MOT · eng_USA_Bates/nan28.cha, line 546 · Nan 2;04
  1. CHIyeah # this go xxx .
    MOTwhat do you think ?
    MOT*MOT: should we put some little people in them ?
    CHIyeah .
    MOTwait # if we move them down this way they'll fit .
  2. MOThere's some more .
    CHIok .
    MOT*MOT: should we keep putting people in them ?%mor: v:aux|should pro|we v|keep part|put-PROG n|person&PL prep|in pro|them ?
    CHIyeah .
    MOTthere's a person .
  3. MOTa couple in there ?
    CHIum yeah .
    MOT*MOT: where should we put the rooster ?
    CHIxxx .
    CHIin there .
  4. MOTok # let's take +...
    MOTremember this is how the one you got works too .
    MOT*MOT: should +...
    MOTwhere should we put the people ?
    MOTwe can put some of them in the car .
  5. MOTremember this is how the one you got works too .
    MOTshould +...
    MOT*MOT: where should we put the people ?
    MOTwe can put some of them in the car .
    CHIyeah .
  6. MOTput him in there ?
    CHIyeah .
    MOT*MOT: should I take the yellow one off or you want to put that on top ?
    MOToh # you can put that on top if you want .
    CHIno .

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. Nan eng_USA_Bates16.39
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Bates/nan28.chaNan 2;4.4276716.39

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. should7 · 100.0%