+ hN &^RIHt!RR4tR#)) defaultdictcTa]tRt^ toRtR RltRtR RltR RltRt Rt R t Vt R#) MinimalSeta Find contexts where more than one possible target value can appear. E.g. if targets are word-initial letters, and contexts are the remainders of words, then we would like to find cases like "fat" vs "cat", and "training" vs "draining". If targets are parts-of-speech and contexts are words, then we would like to find cases like wind (noun) 'air in rapid motion', vs wind (verb) 'coil, wrap'. Nc \4Vn\4Vn\\4Vn/VnV'd!VFwr#pVP W#V4K R#R#)z Create a new minimal set. :param parameters: The (context, target, display) tuples for the item :type parameters: list(tuple(str, str, str)) N)set_targets _contextsr_seen _displaysadd)self parameterscontexttargetdisplays&& 6/usr/lib/python3/dist-packages/nltk/misc/minimalset.py__init__MinimalSet.__init__sN  %  ,6('2-7 c VPV,PV4VPPV4VPPV4W0PW3&R#)a8 Add a new item to the minimal set, having the specified context, target, and display form. :param context: The context in which the item of interest appears :type context: str :param target: The item of interest :type target: str :param display: The information to be reported for each item :type display: str N)r r r rr )r rrrs&&&&rr MinimalSet.add&sR 7' 7# &!-4()rc VPUu.uF(p\VPV,4V8gK&VNK* up#uupi)z Determine which contexts occurred with enough distinct targets. :param minimum: the minimum number of distinct target forms :type minimum: int :rtype: list )r lenr )r minimumcs&& rcontextsMinimalSet.contexts<s6 >>K>aSA-?7-J>KKKs #AAcRW3VP9dVPW3,#V#N)r )r rrdefaults&&&&rrMinimalSet.displayFs(   .>>7"34 4Nrc.pVPF/pVPW4pV'gKVPV4K1 V#r)rrappend)r rresultrxs&& r display_allMinimalSet.display_allLs;mmF W-Aq a $ rcVP#r)r)r s&rtargetsMinimalSet.targetsTs }}r)r r r rr))) __name__ __module__ __qualname____firstlineno____doc__rr rrr&r)__static_attributes____classdictcell__) __classdict__s@rrr s.3 4,L rrN) collectionsrrrrr7s$JJr