Created class to strip documents from BNC using one of three tags:
- s - too small
- p - right size, excludes speech
- bncdoc - too big, variable
It then parses the paragraph with minipar.
Tried getting topic WSD to work with JCN from Pedersen's IC file and 3.0 structure, but it gave horrible results.
Power went out, so parser died. THought that I should also be doing stemming and writing out LDA counts. Stemming will be:
- See if morphy or the Porter stemmer have suggestions
- If it's in WordNet and the original string isn't, keep it and count it
- Get BNC parsing started (office)
Added a stoplist and excluding words of less than length 3. Problem with program using isWord taking string arguments rather than lists, added an assert. Started running all the jobs on office computer.
- Go back to using Pedersen (laptop)
The interpreter is working, but the offsets don't match up to the answer file. Will debug tomorrow.
- Cluster WordNet (cluster)
Nothing done on this. Had an idea of using Huffman codes, but that doesn't make sense without sense frequency. Need to change clustering method to attach less frequent cluster to more frequent one (at the root? or at the most linked to synset?)
Need to regenerate answer file from Semcor after discovering that 2.1 and 2.0 aren't getting along together. There's a new Semcor from Rada, so that should help. Also concerned that a bad mapping might have hurt LDAWN.
Mapping was rather difficult (well, more annoying than difficult); took all day.
Something messed up my office computer. Need to rebuild the filesystem. Hopefully parsing was not lost. Discovered that using new semcor file not as easy as I thought, will need to create new vocab, clean up the code, etc.
Restarted the parsing (after power outage).
Running 1 / 10 on cycles. Need to use disk space more efficiently, so using the LDA assignments and the original dat file to do the topic frequencies.
Discovered that new semcor splitting program isn't quite working:
6006:1 9656:1 41913:3 17850:1 46014:1 12223:1 39328:1 53189:1 46022:1 7115:1 35277:1 39888:1 9720:2 59347:1 980:1 20952:1 40921:1 19930:1 46046:1 49633:1 55272:1 17387:1 59884:1 14589:2 17909:2 53238:1 1016:1 11258:2 55551:2 26110:1 14847:100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
Means that something is messed up.
Wrote script to automatically create topic files trained on bnc and then applied to semcor.