diff --git a/models/Zero-Shot Transfer Learning for Event Extraction/data/amrPostProcessing.jar b/models/Zero-Shot Transfer Learning for Event Extraction/data/amrPostProcessing.jar
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diff --git a/models/Zero-Shot Transfer Learning for Event Extraction/data/amrTranslator.jar b/models/Zero-Shot Transfer Learning for Event Extraction/data/amrTranslator.jar
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diff --git a/models/Zero-Shot Transfer Learning for Event Extraction/data/assignSentId.jar b/models/Zero-Shot Transfer Learning for Event Extraction/data/assignSentId.jar
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diff --git a/models/Zero-Shot Transfer Learning for Event Extraction/data/prepareArgPrediction.jar b/models/Zero-Shot Transfer Learning for Event Extraction/data/prepareArgPrediction.jar
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diff --git a/models/Zero-Shot Transfer Learning for Event Extraction/data/removeXmlTag.jar b/models/Zero-Shot Transfer Learning for Event Extraction/data/removeXmlTag.jar
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diff --git a/models/Zero-Shot Transfer Learning for Event Extraction/data/rsd2ltf.py b/models/Zero-Shot Transfer Learning for Event Extraction/data/rsd2ltf.py
new file mode 100644
index 0000000..8e21162
--- /dev/null
+++ b/models/Zero-Shot Transfer Learning for Event Extraction/data/rsd2ltf.py	
@@ -0,0 +1,233 @@
+#encoding=utf-8
+import os
+import argparse
+import sys
+import itertools
+import xml.dom.minidom
+import xml.etree.ElementTree as ET
+import codecs
+
+# dirty import from current dir
+script_dirname = os.path.dirname(os.path.abspath(__file__))
+sys.path.append(script_dirname)
+from tokenizer import Tokenizer
+
+
+def rsd2ltf(rsd_str, doc_id,
+            seg_option='linebreak',
+            tok_option='unitok',
+            re_segment=False):
+    tokenizer = Tokenizer(seg_option, tok_option)
+
+    if re_segment:
+        # running segmentation and tokenization, then re-segment the tokenized
+        # sentences (use space to concatenate tokens. this solves segmentation
+        # problem, e.g. How are you?I'm fine.).
+        sents = tokenizer.run_segmenter(rsd_str)
+        raw_tokens = tokenizer.run_tokenizer(sents)
+
+        # re-segment tokenized sentence
+        num_sent_reseg = 0
+        tokens = []
+        for i, t in enumerate(raw_tokens):
+            reseg = [item.split() for item in tokenizer.run_segmenter(' '.join(t))]
+            if len(reseg) > 1:
+                num_sent_reseg += 1
+
+            tokens += reseg
+
+        # compute offset for each token
+        indexer = 0
+        token_offset = []
+        for i, t in enumerate(itertools.chain(*tokens)):
+            while not rsd_str[indexer:].startswith(t) and \
+                            indexer < len(rsd_str):
+                indexer += 1
+            if indexer < len(rsd_str):
+                t_start = indexer
+                t_end = t_start + len(t) - 1
+                assert rsd_str[t_start:t_end + 1] == t, \
+                    "re_segment token offset not match %s-%d" % (doc_id, i)
+                token_offset.append((t_start, t_end))
+                indexer = t_end + 1
+
+        assert len(token_offset) == len(list(itertools.chain(*tokens))), \
+            "re_segment tokenization offset error in: %s" % doc_id
+
+        # recover sent using tokens
+        sents = []
+        prev_token_end = token_offset[0][0]-1
+        token_index = 0
+        for i, t in enumerate(tokens):
+            sent = ''
+            for j, item in enumerate(t):
+                if j == 0:
+                    prev_token_end = token_offset[token_index][0] - 1
+
+                sent += ' ' * (token_offset[token_index][0] - prev_token_end - 1) + item
+
+                prev_token_end = token_offset[token_index][1]
+
+                token_index += 1
+
+            assert sent in rsd_str, \
+                're_segment sentence offset error.'
+
+            sents.append(sent)
+
+    else:
+        # running segmentation and tokenization
+        sents = tokenizer.run_segmenter(rsd_str)
+        tokens = tokenizer.run_tokenizer(sents)
+
+    # generate offset for sentences and tokens
+    indexer = 0
+    sent_offset = []
+    for i, s in enumerate(sents):
+        while not rsd_str[indexer:].startswith(s) and indexer < len(rsd_str):
+            indexer += 1
+        if indexer < len(rsd_str):
+            sent_start = indexer
+            sent_end = sent_start + len(s) - 1
+            assert rsd_str[sent_start:sent_end+1] == s, \
+                "sentence offset not match %s-%d" % (doc_id, i)
+            sent_offset.append((sent_start, sent_end))
+            indexer = sent_end + 1
+
+    assert len(sent_offset) == len(sents), \
+        "sentence segmentation offset error in: %s" % doc_id
+
+    token_offsets = []
+    for i, tok in enumerate(tokens):
+        sent_text = sents[i]
+        indexer = 0
+        t_offset = []
+        for j, t in enumerate(tok):
+            while not sent_text[indexer:].startswith(t) and \
+                            indexer < len(sent_text):
+                indexer += 1
+            if indexer < len(sent_text):
+                t_start = indexer
+                t_end = t_start + len(t) - 1
+                assert sent_text[t_start:t_end+1] == t, \
+                    "token offset not match %s-%d-%d" % (doc_id, i, j)
+                t_offset.append((t_start, t_end))
+                indexer = t_end + 1
+        token_offsets.append(t_offset)
+
+        assert len(t_offset) == len(tok), \
+            "tokenization offset error in: %s-%d" % (doc_id, i)
+
+    # convert seg/tok result to ltf
+    root = ET.Element('LCTL_TEXT')
+    doc_element = ET.Element('DOC', {'id': doc_id})
+    text_element = ET.Element('TEXT')
+    root.append(doc_element)
+    doc_element.append(text_element)
+
+    for i in range(len(sents)):
+        seg_text = sents[i]
+        seg_start_char = sent_offset[i][0]
+        seg_end_char = sent_offset[i][1]
+
+        seg_id = '%s-%s' % (doc_id, str(i))
+
+        seg_element = ET.Element('SEG', {'id': seg_id,
+                                         'start_char': str(seg_start_char),
+                                         'end_char': str(seg_end_char)})
+        original_text_element = ET.Element('ORIGINAL_TEXT')
+        original_text_element.text = seg_text
+        seg_element.append(original_text_element)
+
+        for j in range(len(tokens[i])):
+            token_id = 'token-%d-%d' % (i, j)
+            tok_text = tokens[i][j]
+            if not tok_text:
+                continue
+            tok_start_char = int(token_offsets[i][j][0]) + seg_start_char
+            tok_end_char = int(token_offsets[i][j][1]) + seg_start_char
+
+            assert rsd_str[tok_start_char:tok_end_char+1] == tok_text
+
+            token_element = ET.Element('TOKEN',
+                                       {'id': token_id,
+                                        'start_char': str(tok_start_char),
+                                        'end_char': str(tok_end_char)})
+            token_element.text = tok_text
+            seg_element.append(token_element)
+
+        text_element.append(seg_element)
+
+    return root
+
+
+def write2file(ltf_root, out_file):
+    # pretty print xml
+    root_str = ET.tostring(ltf_root, 'utf-8')
+    f_xml = xml.dom.minidom.parseString(root_str)
+    pretty_xml_as_string = f_xml.toprettyxml(encoding="utf-8")
+    f = open(out_file, 'wb')
+    f.write(pretty_xml_as_string)
+    f.close()
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument('rsd_input', type=str,
+                        help='input rsd file path or directory.')
+    parser.add_argument('ltf_output', type=str,
+                        help='output ltf file path or directory.')
+    t = Tokenizer()
+    parser.add_argument('--seg_option', default='linebreak',
+                        help="segmentation options: %s (default is linebreak)" %
+                             ', '.join(t.segmenters.keys()))
+    parser.add_argument('--tok_option', default='unitok',
+                        help="tokenization options: %s (default is unitok)" %
+                             ', '.join(t.tokenizers.keys()))
+    parser.add_argument('--extension', default='.rsd.txt',
+                        help="extension of rsd file")
+    parser.add_argument('--re_segment', action='store_true', default=False,
+                        help='first run tokenizaiton, and then segmentation.')
+
+    args = parser.parse_args()
+
+    input_rsd = args.rsd_input
+    output_ltf = args.ltf_output
+    seg_option = args.seg_option
+    tok_option = args.tok_option
+    extension = args.extension
+    re_segment = args.re_segment
+
+    rsd_files = []
+    output_files = []
+    if os.path.isdir(input_rsd):
+        assert os.path.isdir(output_ltf)
+
+        for fn in os.listdir(input_rsd):
+            if extension not in fn:
+                continue
+            rsd_files.append(os.path.join(input_rsd, fn))
+            output_files.append(os.path.join(output_ltf,
+                                             fn.replace(extension, '.ltf.xml')))
+    else:
+        rsd_files = [input_rsd]
+        output_files = [output_ltf]
+
+    for k, rsd_f in enumerate(rsd_files):
+        try:
+            rsd_str = codecs.open(rsd_f, 'r', 'utf-8').read()
+
+            doc_id = os.path.basename(rsd_f).replace(extension, '')
+
+            ltf_root = rsd2ltf(rsd_str, doc_id, seg_option, tok_option,
+                               re_segment)
+
+            write2file(ltf_root, output_files[k])
+
+        except AssertionError as e:
+            print(e)
+
+        sys.stdout.write('%d files processed.\r' % k)
+        sys.stdout.flush()
+
+    sys.stdout.write('%d files processed.' % len(rsd_files))
diff --git a/models/Zero-Shot Transfer Learning for Event Extraction/data/sentenceExtractor.jar b/models/Zero-Shot Transfer Learning for Event Extraction/data/sentenceExtractor.jar
new file mode 100644
index 0000000..be997ef
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diff --git a/models/Zero-Shot Transfer Learning for Event Extraction/data/tokenizer.py b/models/Zero-Shot Transfer Learning for Event Extraction/data/tokenizer.py
new file mode 100644
index 0000000..65cdf41
--- /dev/null
+++ b/models/Zero-Shot Transfer Learning for Event Extraction/data/tokenizer.py	
@@ -0,0 +1,248 @@
+#encoding=utf-8
+import os
+import jieba
+import nltk
+import re
+import itertools
+import unicodedata as ud
+
+
+class Tokenizer(object):
+    def __init__(self, seg_option="linebreak", tok_option="unitok"):
+        self.segmenters = {'linebreak': self.seg_linebreak,
+                           'nltk': self.seg_nltk,
+                           'cmn': self.seg_cmn,
+                           'edl_spanish': self.seg_edl_spanish,
+                           'edl_cmn': self.seg_edl_cmn,
+                           'nltk+linebreak': self.seg_nltk_linebreak,
+                           'tigrinya': self.seg_tigrinya
+                           }
+        self.tokenizers = {'unitok': self.tok_unitok,
+                           'unitok_cut': self.tok_unitok_cut,
+                           'regexp': self.tok_regexp,
+                           'nltk_wordpunct': self.tok_nltk_wordpunct,
+                           'space': self.tok_space,
+                           'char': self.tok_char,
+                           'jieba': self.tok_jieba,
+                           }
+
+        self.root_dir = os.path.dirname(os.path.abspath(__file__))
+
+        self.seg_option = seg_option
+        self.tok_option = tok_option
+
+        # initialize jieba cn tok
+        if tok_option == 'jieba':
+            jieba.initialize()
+
+    def run_segmenter(self, plain_text):
+        # right strip plain text
+        plain_text = plain_text.rstrip()
+
+        # run segmenter
+        sents = self.segmenters[self.seg_option](plain_text)
+
+        sents = [s for s in sents if s.strip()]
+
+        return sents
+
+    def run_tokenizer(self, sents):
+        # right strip each sent
+        for i in range(len(sents)):
+            sents[i] = sents[i].rstrip()
+
+        # run tokenizer
+        tokenized_sents = self.tokenizers[self.tok_option](sents)
+
+        for i, s in enumerate(tokenized_sents):
+            s = [t for t in s if t.strip()]
+            tokenized_sents[i] = s
+
+        return tokenized_sents
+
+    #
+    # segmenters
+    #
+    def seg_linebreak(self, plain_text):
+        """
+        use "\n" as delimiter
+        :param plain_text:
+        :return:
+        """
+        result = [item.strip() for item in plain_text.split('\n') if item.strip()]
+
+        return result
+
+    def seg_nltk(self, plain_text):
+        """
+        use nltk default segmenter
+        :param plain_text:
+        :return:
+        """
+        result = [item.strip() for item in nltk.sent_tokenize(plain_text)]
+
+        return result
+
+    def seg_nltk_linebreak(self, plain_text):
+        """
+        use nltk segmenter and then use "\n" as delimiter to re-segment.
+        :param plain_text:
+        :return:
+        """
+        nltk_result = '\n'.join(self.seg_nltk(plain_text))
+        linebreak_result = self.seg_linebreak(nltk_result)
+
+        return linebreak_result
+
+    def seg_cmn(self, plain_text):
+        """
+        use Chinese punctuation as delimiter
+        :param plain_text:
+        :return:
+        """
+        res = []
+        sent_end_char = [u'。', u'！', u'？']
+        current_sent = ''
+        for i, char in enumerate(list(plain_text)):
+            if char in sent_end_char or i == len(list(plain_text)) - 1:
+                res.append(current_sent + char)
+                current_sent = ''
+            else:
+                current_sent += char
+
+        return [item.strip() for item in res]
+
+    def seg_edl(self, plain_text, seg_option):
+        # replace \n with ' ' because of the fix line length of edl data
+        # plain_text = plain_text.replace('\n', ' ')
+
+        # do sentence segmentation
+        if seg_option == 'edl_spanish':
+            # use nltk sent tokenization for spanish
+            tmp_seg = nltk.sent_tokenize(plain_text)
+        if seg_option == 'edl_cmn':
+            # use naive sent tokenization for chinese
+            tmp_seg = self.seg_cmn(plain_text)
+
+        # recover \n after xml tag
+        recovered_tmp_seg = []
+        for sent in tmp_seg:
+            sent = sent.replace('> ', '>\n').replace(' <', '\n<')
+            sent = sent.split('\n')
+            recovered_tmp_seg += [item.strip() for item in sent]
+
+        return recovered_tmp_seg
+
+    def seg_edl_spanish(self, plain_text):
+        return self.seg_edl(plain_text, 'edl_spanish')
+
+    def seg_edl_cmn(self, plain_text):
+        return self.seg_edl(plain_text, 'edl_cmn')
+
+    def seg_tigrinya(self, plain_text):
+        result = [item.strip() for item in plain_text.split('\n') if
+                  item.strip()]
+
+        updated_result = []
+        for r in result:
+            if '።' in r:
+                sents = []
+                start = 0
+                for i, char in enumerate(r):
+                    if char == '።':
+                        sents.append(r[start:i+1])
+                        start = i + 1
+                updated_result += sents
+            else:
+                updated_result.append(r)
+
+        return updated_result
+
+    #
+    # tokenizers
+    #
+    def tok_unitok(self, sents):
+        res = []
+        for s in sents:
+            s = unitok_tokenize(s).split()
+            res.append(s)
+
+        return res
+
+    def tok_unitok_cut(self, sents):
+        res = []
+        num_sent_cut = 0
+        for s in sents:
+            s = unitok_tokenize(s).split()
+            if len(s) > 80:
+                sub_sents = [item.split() for item in nltk.sent_tokenize(' '.join(s))]
+                assert sum([len(item) for item in sub_sents]) == len(s)
+
+                # sub_sent = [list(group) for k, group in
+                #             itertools.groupby(s, lambda x: x == ".") if not k]
+                res += sub_sents
+                if len(sub_sents) > 1:
+                    num_sent_cut += 1
+            else:
+                res.append(s)
+        print('%d sentences longer than 80 and cut by delimiter ".".')
+        return res
+
+    def tok_regexp(self, sents):
+        result = []
+        for s in sents:
+            tokenizer = nltk.tokenize.RegexpTokenizer('\w+|\$[\d\.]+|\S+')
+            tokenization_out = tokenizer.tokenize(s)
+            result.append(tokenization_out)
+
+        return result
+
+    def tok_nltk_wordpunct(self, sents):
+        result = []
+        for s in sents:
+            tokenizer = nltk.tokenize.WordPunctTokenizer()
+            tokenization_out = tokenizer.tokenize(s)
+            result.append(tokenization_out)
+        return result
+
+    def tok_space(self, sents):
+        result = []
+        for s in sents:
+            tokenization_out = s.split(' ')
+            result.append(tokenization_out)
+        return result
+
+    def tok_char(self, sents):
+        result = []
+        for s in sents:
+            tokenization_out = list(s)
+            result.append(tokenization_out)
+        return result
+
+    def tok_jieba(self, sents):
+        result = []
+        for s in sents:
+            raw_tokenization_out = list(jieba.cut(s))
+            result.append(raw_tokenization_out)
+        return result
+
+
+# by Jon May
+def unitok_tokenize(data):
+    toks = []
+    for offset, char in enumerate(data):
+        cc = ud.category(char)
+        # separate text by punctuation or symbol
+        if char in ['ʼ', '’', '‘', '´', '′', "'"]:  # do not tokenize oromo apostrophe
+            toks.append(char)
+        elif cc.startswith("P") or cc.startswith("S") \
+                or char in ['።', '፡']:  # Tigrinya period and comma
+            toks.append(' ')
+            toks.append(char)
+            toks.append(' ')
+        else:
+            toks.append(char)
+
+    toks = [item for item in ''.join(toks).split() if item]
+
+    return ' '.join(toks)
\ No newline at end of file