{"url":"/dataset/jerichoworld","name":"JerichoWorld","full_name":null,"description_markdown":"**JerichoWorld**  is a dataset that enables the creation of learning agents that can build knowledge graph-based world models of interactive narratives. Interactive narratives -- or text-adventure games -- are partially observable environments structured as long puzzles or quests in which an agent perceives and interacts with the world purely through textual natural language. Each individual game typically contains hundreds of locations, characters, and objects -- each with their own unique descriptions -- providing an opportunity to study the problem of giving language-based agents the structured memory necessary to operate in such worlds. \r\n\r\nJerichoWorld provides 24,198 mappings between rich natural language observations and: (1) knowledge graphs that reflect the world state in the form of a map; (2) natural language actions that are guaranteed to cause a change in that particular world state. The training data is collected across 27 games in multiple genres and contains a further 7,836 heldout instances over 9 additional games in the test set.","description_withheld":null,"homepage":"https://github.com/JerichoWorld/JerichoWorld","introduced_date":"2021-06-17","introduced_date_note":null,"introduced_by":{"paper":"/paper/modeling-worlds-in-text","title":"Modeling Worlds in Text","first_author":"Prithviraj Ammanabrolu","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Knowledge Graphs","url":"/task/knowledge-graphs","datasets_with_task":"/datasets/task/knowledge-graphs"},{"name":"Action Parsing","url":"/task/action-parsing","datasets_with_task":"/datasets/task/action-parsing"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["JerichoWorld"],"data_loaders":[],"num_papers_in_archive":6,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/knowledge-graphs-on-jerichoworld","task":"Knowledge Graphs","dataset_variant":"JerichoWorld","rows":5,"metrics":["Set accuracy"],"first_row_in_archive_order":{"model":"Worldformer","paper":"/paper/learning-knowledge-graph-based-world-models","metrics":{"Set accuracy":"39.15"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/action-parsing-on-jerichoworld","task":"Action Parsing","dataset_variant":"JerichoWorld","rows":3,"metrics":["Set accuracy"],"first_row_in_archive_order":{"model":"Worldformer","paper":"/paper/learning-knowledge-graph-based-world-models","metrics":{"Set accuracy":"23.22"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/learning-knowledge-graph-based-world-models","title":"Learning Knowledge Graph-based World Models of Textual Environments","date":"2021-06-17","rows_on_this_dataset":4,"code_links":0,"syntology":null},{"paper":"/paper/modeling-worlds-in-text-1","title":"Modeling Worlds in Text","date":"2021-05-21","rows_on_this_dataset":4,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}