30-11-2024, 11:03 AM
Results of the "LOOP" grammar applied to reference transliteration RF1a-n
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The grammar I used is exactly the same as the one of post #21, see there for some additional remarks about its construction. I just changed back the name from WordChunks to LOOP, this because I realized I had mis-appropriated ReneZ's 'word chunk' and used it as a proper name for my grammar, which sureloy is not appropiate. Apologies to @ReneZ!
*** At the risk of being pedant, I want to stress again that the grammar is just one possibility inside a broad class of "LOOP" grammars, which can have many variations but always the same basic structure and are all +- equivalent as coverage goes (efficiency is not a concern here), but which will parse each word type in possibly different ways. And I'd also notice a grammar which loop a chunk can be tricky in this regard, ie.: we could rotate the basic loop chunk of one position to the left, so the "eee ee e" slot is now at the beginning, while the "ch sh" slot goes at the end. This form is very counter-intuitive at first sight, but given the looping mechanism it actually makes little difference to the overall coverage. It will however parse the word types in a different way, ie. 'chedy' will be parsed as [ch][ed]y, with two chunks, while before it was just [ched]y, in one chunk ***
Methodological note: I added 'b', 'j', 'u' to the list of 'rare' characters. They were not present in the transcription I used previously.
Coverage is 98.85% (excluding word types withy 'rare' characters): 7939 word types found on a total of 8031, a total of 92 word types are missed. Efficiency is abysmal, but not of concern in this context. The first word miss is 'oqokain', 2 occurences. All the other word types with at least 2 occurrences are found, as are >97% of the words appearing only once (I don't have an exact count for this). As before, the missed word types have a 'q' not in the first position, or they would require more than 4 word chunks.
This is the Excel file with all the data:
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The grammar I used is exactly the same as the one of post #21, see there for some additional remarks about its construction. I just changed back the name from WordChunks to LOOP, this because I realized I had mis-appropriated ReneZ's 'word chunk' and used it as a proper name for my grammar, which sureloy is not appropiate. Apologies to @ReneZ!
*** At the risk of being pedant, I want to stress again that the grammar is just one possibility inside a broad class of "LOOP" grammars, which can have many variations but always the same basic structure and are all +- equivalent as coverage goes (efficiency is not a concern here), but which will parse each word type in possibly different ways. And I'd also notice a grammar which loop a chunk can be tricky in this regard, ie.: we could rotate the basic loop chunk of one position to the left, so the "eee ee e" slot is now at the beginning, while the "ch sh" slot goes at the end. This form is very counter-intuitive at first sight, but given the looping mechanism it actually makes little difference to the overall coverage. It will however parse the word types in a different way, ie. 'chedy' will be parsed as [ch][ed]y, with two chunks, while before it was just [ched]y, in one chunk ***
Methodological note: I added 'b', 'j', 'u' to the list of 'rare' characters. They were not present in the transcription I used previously.
Coverage is 98.85% (excluding word types withy 'rare' characters): 7939 word types found on a total of 8031, a total of 92 word types are missed. Efficiency is abysmal, but not of concern in this context. The first word miss is 'oqokain', 2 occurences. All the other word types with at least 2 occurrences are found, as are >97% of the words appearing only once (I don't have an exact count for this). As before, the missed word types have a 'q' not in the first position, or they would require more than 4 word chunks.
This is the Excel file with all the data:
You are not allowed to view links. Register or Login to view.