PHPCLANCHILDES with regular expressions

7 matches in 7 utterances

3.43 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (523 utterances, 2,040 words searched).

  1. is it her pants ? MOT · eng_british_Manchester_I/anne24b.cha, line 1118 · Anne 2;06
  2. have you got no pants on ? MOT · eng_british_Manchester_I/anne24b.cha, line 1122 · Anne 2;06
  3. she's got no pants on . MOT · eng_british_Manchester_I/anne24b.cha, line 1126 · Anne 2;06
  4. her pants . MOT · eng_british_Manchester_I/anne24b.cha, line 1130 · Anne 2;06
  5. put your pants on under your trousers . MOT · eng_british_Manchester_I/anne24b.cha, line 1134 · Anne 2;06
  6. where's her pants ? MOT · eng_british_Manchester_I/anne24b.cha, line 1160 · Anne 2;06
  7. do you want a dress or her dungarees back on now she's got pants on ? MOT · eng_british_Manchester_I/anne24b.cha, line 1177 · Anne 2;06
  1. CHI<her pants> [<] .
    MOToh .
    MOT*MOT: is it her pants ?
    MOTexcuse me .
    MOThave you got no pants on ?
  2. MOTis it her pants ?
    MOTexcuse me .
    MOT*MOT: have you got no pants on ?
    MOToh .
    MOTshe's got no pants on .
  3. MOThave you got no pants on ?
    MOToh .
    MOT*MOT: she's got no pants on .
    CHIxxx .
    MOTher pants .
  4. MOTshe's got no pants on .
    CHIxxx .
    MOT*MOT: her pants .
    CHIput your pants on .
    MOTput your pants on under your trousers .
  5. MOTher pants .
    CHIput your pants on .
    MOT*MOT: put your pants on under your trousers .
    MOTshall we take her trousers off ?
    MOToh .
  6. MOTxxx that ribbon's on her dress .
    MOTright then .
    MOT*MOT: where's her pants ?
    CHIwhere's her pants ?
    CHIoh no .
  7. MOThave a look and see if it's in with the food at all .
    MOTwhat do you want her to wear , Anne ?
    MOT*MOT: do you want a dress or her dungarees back on now she's got pants on ?
    CHIdress .
    MOTthat dress ?

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. Anne eng_british_Manchester_I3.43
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_I/anne24b.chaAnne 2;6.042,040773.43

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. pants7 · 100.0%