PHPCLANCHILDES with regular expressions

9 matches in 9 utterances

8.51 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (316 utterances, 1,057 words searched).

  1. look . MOT · eng_british_Manchester_I/becky21b.cha, line 272 · Becky 2;07
  2. look what I found . MOT · eng_british_Manchester_I/becky21b.cha, line 370 · Becky 2;07
  3. somebody's made something already , look . MOT · eng_british_Manchester_I/becky21b.cha, line 601 · Becky 2;07
  4. well look . MOT · eng_british_Manchester_I/becky21b.cha, line 782 · Becky 2;07
  5. put that on there , look . MOT · eng_british_Manchester_I/becky21b.cha, line 1053 · Becky 2;07
  6. can you see in it , look ? MOT · eng_british_Manchester_I/becky21b.cha, line 1077 · Becky 2;07
  7. look . MOT · eng_british_Manchester_I/becky21b.cha, line 1079 · Becky 2;07
  8. there's another one there , look . MOT · eng_british_Manchester_I/becky21b.cha, line 1331 · Becky 2;07
  9. I know they look purple . MOT · eng_british_Manchester_I/becky21b.cha, line 1443 · Becky 2;07
  1. INV<there was> [//] there were two .
    CHImmhm .
    MOT*MOT: look .
    MOTone of them must be lost , Becky .
    CHIone must be lost .
  2. CHIxxx .
    MOTvery very delicate , aren't they ?
    MOT*MOT: look what I found .
    CHIwhat's there ?
    CHIxxx .
  3. CHIoh no .
    CHIxxx .
    MOT*MOT: somebody's made something already , look .
    MOThaven't they ?
    CHIwho was that , Mum ?
  4. MOTit's not big enough .
    CHIwhy ?
    MOT*MOT: well look .
    MOTwe've got tigers yet .
    MOTand a monkey .
  5. MOTxxx .
    MOTthere .
    MOT*MOT: put that on there , look .
    MOTlike that .
    MOTthere .
  6. MOTis it finished, Becky ?
    CHIit's finished .
    MOT*MOT: can you see in it , look ?
    MOTlook .
    MOTwow .
  7. CHIit's finished .
    MOTcan you see in it , look ?
    MOT*MOT: look .
    MOTwow .
    CHIoh .
  8. CHIsorry .
    INVit's alright .
    MOT*MOT: there's another one there , look .
    MOTxxx .
    CHIxxx .
  9. MOTthey're black grapes .
    CHIoh .
    MOT*MOT: I know they look purple .
    MOTbut they're called black grapes .
    INVyeah .

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. Becky eng_british_Manchester_I8.51
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_I/becky21b.chaBecky 2;7.021,057998.51

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. look9 · 100.0%