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add nc_pat/v21 files and updated README.md

README.md

@@ -99,20 +99,34 @@ The 12 diagnostic/warm-up tasks are:
 - car_cdr_seq_path_tuc      (same task as car_cdr_seq_path, but requires mapping lowercase fillers to their uppercase tokens)
 ```
 
-There are 14 core tasks are:
+There are 22 core tasks are:
 ```
 - active_active_stb         (active sentence translation, from sentence to parenthesized tree form, both directions)
 - active_active_stb_40k     (same task as active_active_stb, but train samples increased from 10K to 40K)
+
+- active_logical_ssb        (active to logical sentence translation, in both directions)
+- active_logical_ssb_40k    (same task as active_logical_ssb, but train samples increased from 10K to 40K)
 - active_logical_ttb        (active to logical tree translation, in both directions)
 - active_logical_ttb_40k    (same task as active_logical_ttb, but train samples increased from 10K to 40K)
+
 - active_passive_ssb        (active to passive sentence translation, in both directions)
 - active_passive_ssb_40k    (same task as active_passive_ssb, but train samples increased from 10K to 40K)
 - active_passive_ttb        (active to passive tree translation, in both directions)
 - active_passive_ttb_40k    (same task as active_passive_ttb, but train samples increased from 10K to 40K)
+
+- actpass_logical_ss        (mixture of active to logical and passive to logical sentence translations, single direction)
+- actpass_logical_ss_40k    (same task as actpass_logical_ss, but train samples increased from 10K to 40K)
 - actpass_logical_tt        (mixture of active to logical and passive to logical tree translations, single direction)
 - actpass_logical_tt_40k    (same task as actpass_logical_tt, but train samples increased from 10K to 40K)
+
+- logical_logical_stb       (logical form sentence translation, from sentence to parenthesized tree form, both directions)
+- logical_logical_stb_40k   (same task as logical_logical_stb, but train samples increased from 10K to 40K)
+
+- passive_logical_ssb       (passive to logical sentence translation, in both directions)
+- passive_logical_ssb_40k   (same task as passive_logical_ssb, but train samples increased from 10K to 40K)
 - passive_logical_ttb       (passive to logical tree translation, in both directions)
 - passive_logical_ttb_40k   (same task as passive_logical_ttb, but train samples increased from 10K to 40K)
+
 - passive_passive_stb       (passive sentence translation, from sentence to parenthesized tree form, both directions)
 - passive_passive_stb_40k   (same task as passive_passive_stb, but train samples increased from 10K to 40K)
 ```
@@ -125,6 +139,7 @@ Most tasks have the following splits:
   - test
   - ood_new
   - ood_long
+  - ood_all
   
 Here is a table showing how the number of examples varies by split (for most tasks):
 
@@ -135,6 +150,7 @@ Here is a table showing how the number of examples varies by split (for most tas
 | test          |  1,250                                      |
 | ood_new       |  1,250                                      |
 | ood_long      |  1,250                                      |
+| ood_all       |  1,250                                      |
 
 
 ### Data Instances
@@ -216,6 +232,8 @@ way that generalizes to out of distribution adjective values and lengths.
 
 ## Additional Information
 
+The internal name of this dataset is nc_pat.  
+
 ### Dataset Curators
 
 The dataset by generated from templates designed by Paul Smolensky and Roland Fernandez.

active_active_stb.zip

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active_active_stb_40k.zip

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active_logical_ssb.zip

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active_logical_ssb_40k.zip

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actpass_logical_tt.zip

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basic_sentence_transforms.py

@@ -183,11 +183,11 @@ class BasicSentenceTransforms(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager: datasets.DownloadManager):
         url = self.config.data_url
-        print("_split_generator: url={}".format(url))
+        #print("_split_generator: url={}".format(url))
 
         dl_dir = dl_manager.download_and_extract(url)
         task = self.config_id
-        print("task: {}, dl_dir: {}".format(task, dl_dir))
+        #print("task: {}, dl_dir: {}".format(task, dl_dir))
 
         splits = [
             SplitGenerator(name=Split.TRAIN, gen_kwargs={"data_file": os.path.join(dl_dir, "train.jsonl")}),
@@ -204,7 +204,7 @@ class BasicSentenceTransforms(datasets.GeneratorBasedBuilder):
         return splits
 
     def _generate_examples(self, data_file):
-        print("_generate_examples: data_file: {}".format(data_file))
+        #print("_generate_examples: data_file: {}".format(data_file))
 
         with open(data_file, encoding="utf-8") as f:
             for i, line in enumerate(f):

car_cdr_cons.zip

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