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actors
data
relations
store
utils
.gitignore
README.md
__init__.py
args.py
generator.py

README.md

CLUTRR

Compositional Language Understanding with Text-based Relational Reasoniong

A benchmark dataset generator to test relational reasoning on text.

This work will be presented at Relational Representation Learning Workshop during NIPS 2018. If you use the dataset, please cite our paper:

@ARTICLE{2018arXiv181102959S,
   author = {{Sinha}, K. and {Sodhani}, S. and {Hamilton}, W.~L. and {Pineau}, J.
  },
    title = "{Compositional Language Understanding with Text-based Relational Reasoning}",
  journal = {ArXiv e-prints},
archivePrefix = "arXiv",
   eprint = {1811.02959},
 primaryClass = "cs.CL",
 keywords = {Computer Science - Computation and Language, Computer Science - Artificial Intelligence},
     year = 2018,
    month = nov,
   adsurl = {http://adsabs.harvard.edu/abs/2018arXiv181102959S},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

Dependencies

Generate

python generator.py

Usage

usage: generator.py [-h] [--num_rows NUM_ROWS] [--max_levels MAX_LEVELS]
                    [--min_child MIN_CHILD] [--max_child MAX_CHILD]
                    [--abstracts ABSTRACTS] [--boundary] [--output OUTPUT]
                    [--min_distractor_relations MIN_DISTRACTOR_RELATIONS]
                    [--relation_length RELATION_LENGTH] [--backward]
                    [--train_test_split TRAIN_TEST_SPLIT] [--calc] [-v]

optional arguments:
  -h, --help            show this help message and exit
  --num_rows NUM_ROWS   number of rows
  --max_levels MAX_LEVELS
                        max number of levels
  --min_child MIN_CHILD
                        max number of children per node
  --max_child MAX_CHILD
                        max number of children per node
  --abstracts ABSTRACTS
                        Abstract lines per relation
  --boundary            Boundary in entities
  --output OUTPUT       Prefix of the output file
  --min_distractor_relations MIN_DISTRACTOR_RELATIONS
                        Distractor relations about entities
  --relation_length RELATION_LENGTH
                        Max relation path length
  --backward            if true then consider backward paths too
  --train_test_split TRAIN_TEST_SPLIT
                        Training and testing split
  --calc                Calculate max path
  -v, --verbose         print the paths

CLUTRR v0.1

To generate the dataset used in the paper, use the following arguments

python generate.py --num_rows 5000 --max_levels 3 --min_child 3 --max_child 3 --min_distractor_relations 8 --relation_length 3/4/5/6

Author

Koustuv Sinha