PHPCLANCHILDES with regular expressions

7 matches in 7 utterances

2.87 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (627 utterances, 2,437 words searched).

  1. there's lots of Naughty_Nicks . MOT · eng_british_Manchester_II/ruth32a.cha, line 363 · Ruth 2;10
  2. there's the yoyo . MOT · eng_british_Manchester_II/ruth32a.cha, line 567 · Ruth 2;10
  3. there's one . MOT · eng_british_Manchester_II/ruth32a.cha, line 752 · Ruth 2;10
  4. there's another Poor_Peter . MOT · eng_british_Manchester_II/ruth32a.cha, line 860 · Ruth 2;10
  5. there's an Annie_Apple . MOT · eng_british_Manchester_II/ruth32a.cha, line 951 · Ruth 2;10
  6. there's two Robber_Reds in there . MOT · eng_british_Manchester_II/ruth32a.cha, line 1067 · Ruth 2;10
  7. there's a foot in the way . MOT · eng_british_Manchester_II/ruth32a.cha, line 1511 · Ruth 2;10
  1. CHIyou xxx two Naughty_Nicks .
    MOTI'll give you one .
    MOT*MOT: there's lots of Naughty_Nicks .
    CHII 0have [*] got two Naughty_Nicks .
    MOThave you got two Naughty_Nicks ?
  2. MOTshall we put them in here ?
    CHIyeah .
    MOT*MOT: there's the yoyo .
    MOThow many Yoyo_Men have we got ?
    MOTthree .
  3. CHIyeah .
    CHIyou got one ?
    MOT*MOT: there's one .
    CHIme [*] 0have [*] got two .
    MOTI've got one two three four .
  4. CHIbecause like being Poor_Peter .
    CHIthere 0is [*] another Poor_Peter .
    MOT*MOT: there's another Poor_Peter .
    MOTexcuse me .
    MOTthat is my Poor_Peter .
  5. CHIAnnie_Apples .
    MOThere .
    MOT*MOT: there's an Annie_Apple .
    CHIokay .
    CHIoh xxx .
  6. CHIno .
    MOTI don't have any more Robber_Reds .
    MOT*MOT: there's two Robber_Reds in there .
    CHIwant them in here .
    MOTwell you put them from there into there already .
  7. CHIfoot there .
    MOToh no .
    MOT*MOT: there's a foot in the way .
    MOToh dear .
    CHIaway now .

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. Ruth eng_british_Manchester_II2.87
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/ruth32a.chaRuth 2;10.232,437772.87

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. there's7 · 100.0%