Update README.md

README.md

@@ -21,3 +21,25 @@ Preprocessed training and evaluation data from KiloGram.
 
 KiloGram dataset and code repo: https://github.com/lil-lab/kilogram
 
+---
+# File Formats
+## Training Set
+Texts: `train_*.json` are all in the format of `{tangramName: list(annotations)}`.
+
+Images: Colored images with parts (under `/color`) are named in the format of `tangramName_{idx}.png`, where `idx` corresponds to the index of the annotation in the text file.
+
+## Validation, Development, Heldout Set
+
+Texts: `{whole, part}_{black, color}.json` are in the format of `{"targets": list(imageFileNames), "images": list(imageFileNames), "texts": list(annotations)}`. We flattened all the contexts and concatenated them into one list for each entry. 
+
+E.g. the first 10 elements in `"targets"` are the image file name of the target of the first context repeated 10 times; the first 10 of `"images"` are the image file names in that context; and the first 10 of `"texts"` are the corresponding 10 annotations in that context.
+
+`/controlled` contains experiments with constrained contexts controlled for number of parts, and `/random` contains ones without. (See Appendix A.8 in paper)
+
+`/development/texts/augmented/aug_dev.json` and `images/augmented.tar.bz2` are experiments in the same format as above used to evaluate the effect of adding part information. 
+
+
+Intermediate files:
+
+`*/text/controlled/eval_batch_data.json` are in the format of 
+`{tangramName: {numOfParts: list({"target": [tangramName_{idx}, annotation], "distractors": list(list([tangramName_{idx}, annotation]))})}}`, used to generate controlled experiment jsons. Note: annotations are descriptions concatenated by "#" instead of in natural English.