## Data from "Multi-Domain Goal-Oriented Dialogues (MultiDoGO): Strategies toward Curating and Annotating Large Scale Dialogue Data" ### Repository Structure Under the top level ./data directory, you will find the following two sub-directories: #### 1. unannotated: unannotated human to human conversations from the airline, fastfood, finance, insurance, media, and software domains. Conversations are split by domain and given in TSV format with columns: "conversationId", "turnNumber", "utteranceId", "utterance", "authorRole". #### 2. paper_splits: pre-processed training, development, and test splits for customer turns used to obtain intent classification and slot-labeling results in Table 7 of the paper. As in the paper, we partition these data by annotation granularity, either sentence level (located at ./data/paper_splits/splits_annotated_at_sentence_level) or turn level (located at ./data/paper_splits/splits_annotated_at_turn_level). Under each annotation granularity subdirectory, we provide splits for each domain: airline, fastfood, finance, insurance, media, and software. The splits are labeled as "train.tsv", "dev.tsv", "test.tsv" and contain the following tab separated columns: "conversationId", "turnNumber", "sentenceNumber" (only for sentence level splits), "utteranceId", "utterance", "slot-labels", and "intent". The labels in the slot-labels field are separated by spaces. In the case of multiple intents for a single input, we separate the intents with the special token \