PHPCLANCHILDES with regular expressions

8 matches in 8 utterances

3.97 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (510 utterances, 2,013 words searched).

  1. started raining , has it ? MOT · eng_british_Manchester_I/becky06b.cha, line 442 · Becky 2;01
  2. it has stopped raining . MOT · eng_british_Manchester_I/becky06b.cha, line 458 · Becky 2;01
  3. I think she has . INV · eng_british_Manchester_I/becky06b.cha, line 789 · Becky 2;01
  4. has she ? MOT · eng_british_Manchester_I/becky06b.cha, line 791 · Becky 2;01
  5. has dolly finished her dinner ? MOT · eng_british_Manchester_I/becky06b.cha, line 1494 · Becky 2;01
  6. has she ? MOT · eng_british_Manchester_I/becky06b.cha, line 1498 · Becky 2;01
  7. has Baa_baa got any eyebrows ? MOT · eng_british_Manchester_I/becky06b.cha, line 1636 · Becky 2;01
  8. has he ? MOT · eng_british_Manchester_I/becky06b.cha, line 1642 · Becky 2;01
  1. MOTI don't think it's raining .
    CHIstop raining .
    MOT*MOT: started raining , has it ?
    CHIstop raining .
    MOTit's not raining .
  2. MOTI see .
    MOTyes .
    MOT*MOT: it has stopped raining .
    MOTcan you see what's happened , look ?
    CHIyeah .
  3. MOTand her hattie on ?
    MOTI'm not sure if she's got a hattie .
    INV*INV: I think she has .
    MOThas she ?
    MOTshall we see if we can find it then .
  4. MOTI'm not sure if she's got a hattie .
    INVI think she has .
    MOT*MOT: has she ?
    MOTshall we see if we can find it then .
    INVwww .
  5. MOThave you finished now then ?
    CHIyeah .
    MOT*MOT: has dolly finished her dinner ?
    CHIyeah .
    MOThas she ?
  6. MOThas dolly finished her dinner ?
    CHIyeah .
    MOT*MOT: has she ?
    CHIyeah .
    MOTgood .
  7. MOTeyebrows .
    CHIeyebrows .
    MOT*MOT: has Baa_baa got any eyebrows ?
    CHIyeah .
    CHIyeah .
  8. CHIyeah .
    CHIyeah .
    MOT*MOT: has he ?
    MOTwhere are they ?
    MOTno .

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_I3.97
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_I/becky06b.chaBecky 2;1.302,013883.97

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. has8 · 100.0%