Example - Add SD-Rules Derived from factD

The original Lexical Tools collects 4,467 SD-pairs with 4,110 suffix SD-pairs. These SD-pairs can be used to derive possible SD-rules by following the same approach in the nomD session:

• Identifies possible SD-Rules by stripping the same starting characters of each valid SD-pair generated from factD.
• Select high frequency SD-rules to add to SD-rules set:

  Possible SD-rule from factD	Root	Related	Notes
  $|noun|less$|adj|131|131	Yes	None	Selected
  $|verb|$ion|noun|111|111	Yes	Duplicated	Not selected
  ist$|noun|y$|noun|63|63	Yes	None	Selected
  $|adj|ally$|adv|58|58 => ic$|adj|ically$|adv is used instead => need to verify the root stats	Yes	None	Selected
  $|noun|ful$|adj|58|58	Yes	None	Selected
  c$|adj|s$|noun|54|54 => ic$|adj|is$|noun is used instead => need to verify the root stats	Yes	None	Selected
  on$|noun|ve$|adj|38|38	Yes	None	Not selected due to low frequency (coverage)
  ...	...	...	Not selected due to low frequency (coverage)

• Apply the same procedures to get the optimized set as in add SD-rules from nomD session by using the optimized set of 2.3.4 as new baseline. This task involves:
  • Retrieve all raw SD-pairs from Lexicon (2013) of above four selected SD-rules
  • Tag raw SD-pairs
  • Get stats of SD-pairs of these four SD-rules
  • Add to SD-rules set and find the optimization
  • The total valid SD-Pair no. (TotalYes) needs to be calculated as total valid SD-pair no. from all parent-rules.

  The iterative results are shown as follows:

  ID	New Candidate Rule	Total Yes	Total Rule No.	Rule No.	A. Rate	Occr.	Yes	No	Tbd	SD-Rule	Status	Source	Notes	Sys A. Rate	Sys C. Rate	Sys. Perf	Notes
  2.3.4 (prev. optimized set)		39,197	90	68	60.66%	183	111	72	0	ar$|adj|e$|noun	2013	ORG_RULE	SELF	95.05%	94.60%	1.8965	Baseline
  2.3.4.1	12|99.95%|1931|1930|1|0|ic$|adj|ically$|adv|2013|ORG_FACT|SELF	41,127 = 39,197 + 1930	91	69	60.66%	183	111	72	0	ar$|adj|e$|noun	2013	ORG_RULE	SELF	95.28%	94.85%	1.9013	Better
  2.3.4.2	15|99.64%|559|557|2|0|$|noun|less$|adj|2013|ORG_FACT|SELF	41,684 = 41,127 + 557	92	70	60.66%	183	111	72	0	ar$|adj|e$|noun	2013	ORG_RULE	SELF	95.34%	94.92%	1.9026	Better
  2.3.4.3	40|95.63%|504|482|22|0|ist$|noun|y$|noun|2013|ORG_FACT|SELF	42,166 = 41,684 + 482	93	71	60.66%	183	111	72	0	ar$|adj|e$|noun	2013	ORG_RULE	SELF	95.35%	94.98%	1.9032	Better
  2.3.4.4	49|91.70%|277|254|23|0|ic$|adj|is$|noun|2013|ORG_FACT|SELF	42,420 = 42,166 + 254	94	72	60.66%	183	111	72	0	ar$|adj|e$|noun	2013	ORG_RULE	SELF	95.32%	95.01%	1.9033	Better
  2.3.4.5	55|89.93%|139|125|14|0|$|noun|ful$|adj|2013|ORG_FACT|SELF	42,545 = 42,420 + 125	95	73	60.66%	183	111	72	0	ar$|adj|e$|noun	2013	ORG_RULE	SELF	95.30%	95.02%	1.9033	Best

From above results, all five selected SD-rules (with the highest frequency and precision from factD) improved the system performance. Thus, all these five SD-rles are added to the SD-rule set. Please note that SD-rule ic$|adj|ically$|adv and ic$|adj|is$|noun are suggested SD-rules from their root parent-rule $|adj|ally$|adv and c$|adj|s$|noun, respectively. Both of root parent-rules should be re-evaluated by this system.

The table above shows the iterative results by adding new rules derived from factD step by step. The results show all five selected SD-rules (with the highest frequency from factD) improve the system performance. Thus, all these five SD-rules are added to the SD-rule set to reach better coverage rate (95.02%) and system performance (1.9033) with accuracy rate of 95.30% to include 73 (out of 95) SD-rule in the optimized set. The diagram below shows the system accuracy and coverage curves of this optimized set.