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README.md

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 ---
-license: other
+annotations_creators:
+- machine-generated
+language:
+- en
+language_creators:
+- machine-generated
+license:
+- other
+multilinguality:
+- monolingualfile:///C:/Users/rfernand/Downloads/18599-Final%20PDF-25853-1-10-20220929%20(2).pdf
+pretty_name: Active/Passive/Logical Transforms
+size_categories:
+- 10K<n<100K
+- 1K<n<10K
+- n<1K
+source_datasets:
+- original
+tags:
+- struct2struct
+- tree2tree
+task_categories:
+- text2text-generation
+task_ids: []
 ---
+# Dataset Card for Active/Passive/Logical Transforms
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Dataset Subsets (Tasks)](#data-tasks)
+  - [Dataset Splits](#data-splits)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:**
+- **Repository:** 
+- **Paper:** 
+- **Leaderboard:** 
+- **Point of Contact:** [Roland Fernandez](mailto:[email protected])
+
+### Dataset Summary
+
+This dataset is a synthetic dataset containing structure-to-structure transformation tasks between 
+English sentences in 3 forms: active, passive, and logical.  The dataset also includes several 
+tree-transformation diagnostic/warm-up tasks.
+
+### Supported Tasks and Leaderboards
+
+[TBD]
+
+### Languages
+
+All data is in English.
+
+## Dataset Structure
+
+The dataset consists of several subsets, or tasks. Each task contains a train split, a validation split, and a
+test split, with most tasks also containing two out-of-distruction splits (one for new adjectives and one for longer adjective phrases).  
+
+Each sample in a split contains a source string, a target string, and 0-2 annotation strings.
+
+### Dataset Subsets (Tasks)
+The dataset consists of diagnostic/warm-up tasks and core tasks.  The core tasks represent the translation of English sentences between the active, passive, and logical forms.
+
+The 12 diagnostic/warm-up tasks are:
+
+```
+- car_cdr_cons              (small phrase translation tasks that require only: CAR, CDR, or CAR+CDR+CONS operations)
+- car_cdr_cons_tuc          (same task as car_cdr_cons, but requires mapping lowercase fillers to their uppercase tokens)
+- car_cdr_rcons             (same task as car_cdr_cons, but the CONS samples have their left/right children swapped)
+- car_cdr_rcons_tuc         (same task as car_cdr_rcons, but requires mapping lowercase fillers to their uppercase tokens)
+- car_cdr_seq               (each samples requires 1-4 combinations of CAR and CDR, as identified by the root filler oken)
+- car_cdr_seq_40k           (same task as car_cdr_seq, but train samples increased from 10K to 40K)
+- car_cdr_seq_tuc           (same task as car_cdr_seq, but requires mapping lowercase fillers to their uppercase tokens)
+- car_cdr_seq_40k_tuc       (same task as car_cdr_seq_tuc, but train samples increased from 10K to 40K)
+- car_cdr_seq_path          (similiar to car_cdr_seq, but each needed operation in represented as a node in the left child of the root)
+- car_cdr_seq_path_40k      (same task as car_cdr_seq_path, but train samples increased from 10K to 40K)
+- car_cdr_seq_path_40k_tuc  (same task as car_cdr_seq_path_40k, but requires mapping lowercase fillers to their uppercase tokens)
+- 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:
+```
+- 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_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_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)
+- 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)
+```
+
+### Data Splits
+
+Most tasks have the following splits:
+  - train
+  - validation
+  - test
+  - ood_new
+  - ood_long
+  
+Here is a table showing how the number of examples varies by split (for most tasks):
+
+| Dataset Split | Number of Instances in Split                |
+| ------------- | ------------------------------------------- |
+| train         | 10,000                                      |
+| validation    |  1,250                                      |
+| test          |  1,250                                      |
+| ood_new       |  1,250                                      |
+| ood_long      |  1,250                                      |
+
+
+### Data Instances
+
+For each sample, there is source and target string.  Source and target string are either plain text, or a parenthesized 
+version of a tree, depending on the task.
+
+Here is an example from the *train* split of the *active_passive_ttb* task:
+
+```
+{
+  'source': '( S ( NP ( DET his ) ( AP ( N cat ) ) ) ( VP ( V discovered ) ( NP ( DET the ) ( AP ( ADJ blue ) ( AP ( N priest ) ) ) ) ) )',
+  'target': '( S ( NP ( DET the ) ( AP ( ADJ blue ) ( AP ( N priest ) ) ) ) ( VP ( AUXPS was ) ( VPPS ( V discovered ) ( PPPS ( PPS by ) ( NP ( DET his ) ( AP ( N cat ) ) ) ) ) ) )',
+  'direction': 'forward'
+}
+```
+
+### Data Fields
+
+- `source`: the string denoting the sequence or tree structure to be translated 
+- `target`: the string denoting the gold (aka label) sequence or tree structure  
+
+Optional annotation fields (their presence varies by task):
+
+- `direction`: describes the direction of the translation (forward, backward), relative to the task name 
+- `count` : a string denoting the count of symbolic operations needed (e.g., "s3") to translate the source to the target
+- `class` : a string denoting the type of translation needed
+
+## Dataset Creation
+
+### Curation Rationale
+
+We wanted a dataset comprised of relatively simple English active/passive/logical form translations, where we could focus 
+on two types of out of distribution generalization: longer source sequences and new adjectives.  
+
+### Source Data
+
+[N/A]
+
+#### Initial Data Collection and Normalization
+
+[N/A]
+
+#### Who are the source language producers?
+
+The dataset by generated from templates designed by Paul Smolensky and Roland Fernandez.
+
+### Annotations
+
+Besides the source and target structured sequences, some of the subsets (tasks) contain 1-2 additional columns that
+describe the category and tree depth of each sample.
+
+#### Annotation process
+
+The annotation columns were generated from the each sample template and source sequence.
+
+#### Who are the annotators?
+
+[N/A]
+
+### Personal and Sensitive Information
+
+No names or other sensitive information are included in the data.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+The purpose of this dataset is to help develop models that can translated structured data from one form to another, in a
+way that generalizes to out of distribution adjective values and lengths.
+
+### Discussion of Biases
+
+[TBD]
+
+### Other Known Limitations
+
+[TBD]
+
+## Additional Information
+
+### Dataset Curators
+
+The dataset by generated from templates designed by Paul Smolensky and Roland Fernandez.
+
+### Licensing Information
+
+This dataset is released under the [Permissive 2.0 license](https://cdla.dev/permissive-2-0/). 
+
+### Citation Information
+
+[TBD]
+
+### Contributions
+
+Thanks to [@rfernand2](https://github.com/rfernand2) for adding this dataset.

active_active_stb.zip

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nc_pat.py

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+# nc_pat.py: the HF datasets "loading script" for the NC_PAT dataset (defines configurations/tasks, columns, etc.)
+import os
+import json
+import datasets
+from datasets import Split, SplitGenerator
+
+no_extra = {
+    "source": datasets.Value("string"),
+    "target": datasets.Value("string"),
+}
+
+samp_class = {
+    "source": datasets.Value("string"),
+    "target": datasets.Value("string"),
+    "class": datasets.Value("string"),
+}
+
+count_class = {
+    "source": datasets.Value("string"),
+    "target": datasets.Value("string"),
+    "count": datasets.Value("string"),
+    "class": datasets.Value("string"),
+}
+
+dir_only = {
+    "source": datasets.Value("string"),
+    "target": datasets.Value("string"),
+    "direction": datasets.Value("string"),
+}
+
+configs = [
+    {"name": "car_cdr_cons",
+    "desc": "small phrase translation tasks that require only: CAR, CDR, or CAR+CDR+CONS operations",
+    "features": samp_class},
+
+    {"name": "car_cdr_cons_tuc",
+    "desc": "same task as car_cdr_cons, but requires mapping lowercase fillers to their uppercase tokens",
+    "features": samp_class},
+
+    {"name": "car_cdr_rcons",
+    "desc": "same task as car_cdr_cons, but the CONS samples have their left/right children swapped",
+    "features": samp_class},
+
+    {"name": "car_cdr_rcons_tuc",
+    "desc": "same task as car_cdr_rcons, but requires mapping lowercase fillers to their uppercase tokens",
+    "features": samp_class},
+
+    {"name": "car_cdr_seq",
+    "desc": "each samples requires 1-4 combinations of CAR and CDR, as identified by the root filler token",
+    "features": count_class},
+
+    {"name": "car_cdr_seq_40k",
+    "desc": "same task as car_cdr_seq, but train samples increased from 10K to 40K",
+    "features": count_class},
+
+    {"name": "car_cdr_seq_tuc",
+    "desc": "same task as car_cdr_seq, but requires mapping lowercase fillers to their uppercase tokens",
+    "features": count_class},
+
+    {"name": "car_cdr_seq_40k_tuc",
+    "desc": "same task as car_cdr_seq_tuc, but train samples increased from 10K to 40K",
+    "features": count_class},
+
+    {"name": "car_cdr_seq_path",
+    "desc": "similiar to car_cdr_seq, but each needed operation in represented as a node in the left child of the root",
+    "features": count_class},
+
+    {"name": "car_cdr_seq_path_40k",
+    "desc": "same task as car_cdr_seq_path, but train samples increased from 10K to 40K",
+    "features": count_class},
+
+    {"name": "car_cdr_seq_path_40k_tuc",
+    "desc": "same task as car_cdr_seq_path_40k, but requires mapping lowercase fillers to their uppercase tokens",
+    "features": count_class},
+
+    {"name": "car_cdr_seq_path_tuc",
+    "desc": "same task as car_cdr_seq_path, but requires mapping lowercase fillers to their uppercase tokens",
+    "features": count_class},
+
+    {"name": "active_active_stb",
+    "desc": "active sentence translation, from sentence to parenthesized tree form, both directions",
+    "features": dir_only},
+    
+    {"name": "active_active_stb_40k",
+    "desc": "same task as active_active_stb, but train samples increased from 10K to 40K",
+    "features": dir_only},
+    
+    {"name": "active_logical_ttb",
+    "desc": "active to logical tree translation, in both directions",
+    "features": dir_only},
+    
+    {"name": "active_logical_ttb_40k",
+    "desc": "same task as active_logical_ttb, but train samples increased from 10K to 40K",
+    "features": dir_only},
+    
+    {"name": "active_passive_ssb",
+    "desc": "active to passive sentence translation, in both directions",
+    "features": dir_only},
+    
+    {"name": "active_passive_ssb_40k",
+    "desc": "same task as active_passive_ssb, but train samples increased from 10K to 40K",
+    "features": dir_only},
+    
+    {"name": "active_passive_ttb",
+    "desc": "active to passive tree translation, in both directions",
+    "features": dir_only},
+    
+    {"name": "active_passive_ttb_40k",
+    "desc": "same task as active_passive_ttb, but train samples increased from 10K to 40K",
+    "features": dir_only},
+    
+    {"name": "actpass_logical_tt",
+    "desc": "mixture of active to logical and passive to logical tree translations, single direction",
+    "features": no_extra},
+    
+    {"name": "actpass_logical_tt_40k",
+    "desc": "same task as actpass_logical_tt, but train samples increased from 10K to 40K",
+    "features": no_extra},
+    
+    {"name": "passive_logical_ttb",
+    "desc": "passive to logical tree translation, in both directions",
+    "features": dir_only},
+    
+    {"name": "passive_logical_ttb_40k",
+    "desc": "same task as passive_logical_ttb, but train samples increased from 10K to 40K",
+    "features": dir_only},
+    
+    {"name": "passive_passive_stb",
+    "desc": "passive sentence translation, from sentence to parenthesized tree form, both directions",
+    "features": dir_only},
+    
+    {"name": "passive_passive_stb_40k",
+    "desc": "same task as passive_passive_stb, but train samples increased from 10K to 40K",
+    "features": dir_only},
+]
+
+class NcPatConfig(datasets.BuilderConfig):
+    """BuilderConfig for NC_PAT dataset."""
+
+    def __init__(self, features=None, **kwargs):
+        # Version history:
+        # 0.0.17: Initial version released to HF datasets
+        super().__init__(version=datasets.Version("0.0.17"), **kwargs)
+
+        self.features = features
+        self.label_classes = None
+        self.data_url = "./{}.zip".format(kwargs["name"])
+        self.citation = None
+        self.homepage = None
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=self.description,
+            features=self.features,
+            # No default supervised_keys (as we have to pass both question
+            # and context as input).
+            supervised_keys=None,
+            homepage=self.homepage,
+            citation=self.citation,
+        )
+
+class NcPat(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [NcPatConfig(name=c["name"], description=c["desc"], features=c["features"]) for c in configs]
+    VERSION = datasets.Version("0.0.17")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description="The dataset consists of diagnostic/warm-up tasks and core tasks within this dataset." + 
+                "The core tasks represent the translation of English sentences between the active, passive, and logical forms.",
+            supervised_keys=None,
+            homepage=None,
+            citation=None,
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager):
+        url = self.config.data_url
+        dl_dir = dl_manager.download_and_extract(url)
+        task = self.config_id
+
+        splits = [
+            SplitGenerator(name=Split.TRAIN, gen_kwargs={"data_file": os.path.join(dl_dir, "train.jsonl")}),
+            SplitGenerator(name=Split.VALIDATION, gen_kwargs={"data_file": os.path.join(dl_dir, "dev.jsonl")}),
+            SplitGenerator(name=Split.TEST, gen_kwargs={"data_file": os.path.join(dl_dir, "test.jsonl")}),
+        ]
+
+        if not task.startswith("car_cdr_cons") and not task.startswith("car_cdr_rcons"):
+            splits += [
+                SplitGenerator(name="ood_new", gen_kwargs={"data_file": os.path.join(dl_dir, "ood_new_adj.jsonl")}),
+                SplitGenerator(name="ood_long", gen_kwargs={"data_file": os.path.join(dl_dir, "ood_long_adj.jsonl")}),
+            ]
+
+        return splits
+
+    def _generate_examples(self, data_file):
+        with open(data_file, encoding="utf-8") as f:
+            for i, line in enumerate(f):
+                key = str(i)
+                row = json.loads(line)    
+                yield key, row  
+
+if __name__ == "__main__":
+    # short test 
+    builder = NcPat.BUILDER_CONFIGS[0]
+    print("name: {}, desc: {}".format(builder.name, builder.description))
+

passive_logical_ttb.zip

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passive_passive_stb.zip

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passive_passive_stb_40k.zip

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use.txt

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+Community Data License Agreement - Permissive - Version 2.0
+
+This is the Community Data License Agreement - Permissive, Version 2.0 (the "agreement"). Data Provider(s) and Data Recipient(s) agree as follows:
+
+1. Provision of the Data
+
+1.1. A Data Recipient may use, modify, and share the Data made available by Data Provider(s) under this agreement if that Data Recipient follows the terms of this agreement.
+
+1.2. This agreement does not impose any restriction on a Data Recipient's use, modification, or sharing of any portions of the Data that are in the public domain or that may be used, modified, or shared under any other legal exception or limitation.
+
+2. Conditions for Sharing Data
+
+2.1. A Data Recipient may share Data, with or without modifications, so long as the Data Recipient makes available the text of this agreement with the shared Data.
+
+3. No Restrictions on Results
+
+3.1. This agreement does not impose any restriction or obligations with respect to the use, modification, or sharing of Results.
+
+4. No Warranty; Limitation of Liability
+
+4.1. All Data Recipients receive the Data subject to the following terms:
+
+THE DATA IS PROVIDED ON AN "AS IS" BASIS, WITHOUT REPRESENTATIONS, WARRANTIES OR CONDITIONS OF ANY KIND, EITHER EXPRESS OR IMPLIED INCLUDING, WITHOUT LIMITATION, ANY WARRANTIES OR CONDITIONS OF TITLE, NON-INFRINGEMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.
+
+NO DATA PROVIDER SHALL HAVE ANY LIABILITY FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING WITHOUT LIMITATION LOST PROFITS), HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE DATA OR RESULTS, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.
+
+5. Definitions
+
+5.1. "Data" means the material received by a Data Recipient under this agreement.
+
+5.2. "Data Provider" means any person who is the source of Data provided under this agreement and in reliance on a Data Recipient's agreement to its terms.
+
+5.3. "Data Recipient" means any person who receives Data directly or indirectly from a Data Provider and agrees to the terms of this agreement.
+
+5.4. "Results" means any outcome obtained by computational analysis of Data, including for example machine learning models and models' insights.