Update README.md

README.md

@@ -50,4 +50,60 @@ task_categories:
 - text-classification
 language:
 - en
----
+---
+
+# dstc3
+
+This is a text classification dataset. It is intended for machine learning research and experimentation.
+
+This dataset is obtained via formatting another publicly available data to be compatible with our [AutoIntent Library](https://deeppavlov.github.io/AutoIntent/index.html).
+
+## Usage
+
+It is intended to be used with our [AutoIntent Library](https://deeppavlov.github.io/AutoIntent/index.html):
+
+```python
+from autointent import Dataset
+
+dream = Dataset.from_datasets("AutoIntent/dstc3")
+```
+
+## Source
+
+This dataset is taken from `marcel-gohsen/dstc3` and formatted with our [AutoIntent Library](https://deeppavlov.github.io/AutoIntent/index.html):
+
+```python
+from datasets import load_dataset
+from autointent import Dataset
+
+# load original data
+dstc3 = load_dataset("marcel-gohsen/dstc3")
+
+# extract intent names
+dstc3["test"] = dstc3["test"].filter(lambda example: example["transcript"] != "")
+intent_names = sorted(set(name for intents in dstc3["test"]["intent"] for name in intents))
+intent_names.remove("reqmore")
+dstc3["test"].filter(lambda example: "reqmore" in example["intent"])
+name_to_id = {name: i for i, name in enumerate(intent_names)}
+
+# parse complicated dstc format
+def transform(example: dict):
+    return {
+        "utterance": example["transcript"],
+        "label": [name_to_id[intent_name] for intent_name in example["intent"] if intent_name != "reqmore"],
+    }
+dstc_converted = dstc3["test"].map(transform, remove_columns=dstc3["test"].features.keys())
+
+# format to autointent.Dataset
+intents = [{"id": i, "name": name} for i, name in enumerate(intent_names)]
+utterances = []
+oos_utterances = []
+for rec in dstc_converted.to_list():
+    if len(rec["label"]) == 0:
+        rec.pop("label")
+        oos_utterances.append(rec["utterance"])
+    else:
+        utterances.append(rec)
+oos_records = [{"utterance": ut} for ut in set(oos_utterances)]
+dstc_converted = Dataset.from_dict({"intents": intents, "train": utterances + oos_records})
+```