{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/pivoine-instruction-tuning-for-open-world","title":"PIVOINE: Instruction Tuning for Open-world Information Extraction","arxiv_id":"2305.14898","date":"2023-05-24","proceeding":null,"authors":["Keming Lu","Xiaoman Pan","Kaiqiang Song","Hongming Zhang","Dong Yu","Jianshu Chen"],"abstract":"We consider the problem of Open-world Information Extraction (Open-world IE), which extracts comprehensive entity profiles from unstructured texts. Different from the conventional closed-world setting of Information Extraction (IE), Open-world IE considers a more general situation where entities and relations could be beyond a predefined ontology. More importantly, we seek to develop a large language model (LLM) that is able to perform Open-world IE to extract desirable entity profiles characterized by (possibly fine-grained) natural language instructions. We achieve this by finetuning LLMs using instruction tuning. In particular, we construct INSTRUCTOPENWIKI, a substantial instruction tuning dataset for Open-world IE enriched with a comprehensive corpus, extensive annotations, and diverse instructions. We finetune the pretrained BLOOM models on INSTRUCTOPENWIKI and obtain PIVOINE, an LLM for Open-world IE with strong instruction-following capabilities. Our experiments demonstrate that PIVOINE significantly outperforms traditional closed-world methods and other LLM baselines, displaying impressive generalization capabilities on both unseen instructions and out-of-ontology cases. Consequently, PIVOINE emerges as a promising solution to tackle the open-world challenge in IE effectively.","url_abs":"https://arxiv.org/abs/2305.14898v1","url_pdf":"https://arxiv.org/pdf/2305.14898v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"pivoine-instruction-tuning-for-open-world","repo_url":"https://github.com/lukeming-tsinghua/instruction-tuning-for-open-world-ie","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"instruction-following","task_name":"Instruction Following"},{"task_slug":"language-modeling","task_name":"Language Modeling"},{"task_slug":"language-modelling","task_name":"Language Modelling"},{"task_slug":"large-language-model","task_name":"Large Language Model"}],"methods":[{"method_slug":"bloom","method_name":"BLOOM"}],"datasets_introduced":[{"slug":"instructopenwiki","name":"InstructOpenWiki","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2305.14898","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.14898"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/lukeming-tsinghua/instruction-tuning-for-open-world-ie","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"unverified":4},"by_repo_kind":{"official":{"samples":4,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"cdbbe8bc4084f31a","entry":"aug_default","repo":"lukeming-tsinghua/instruction-tuning-for-open-world-ie","repo_kind":"official","path":"processed_pretrained_data/augment_utils.py","file_url":"https://github.com/lukeming-tsinghua/instruction-tuning-for-open-world-ie/blob/HEAD/processed_pretrained_data/augment_utils.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"cdbbe8bc4084f31a"}},{"code_sha256_prefix":"66dd6517939f44a3","entry":"aug_ent_num","repo":"lukeming-tsinghua/instruction-tuning-for-open-world-ie","repo_kind":"official","path":"processed_pretrained_data/augment_utils.py","file_url":"https://github.com/lukeming-tsinghua/instruction-tuning-for-open-world-ie/blob/HEAD/processed_pretrained_data/augment_utils.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"66dd6517939f44a3"}},{"code_sha256_prefix":"38cb4bd179a0bf91","entry":"augmentation","repo":"lukeming-tsinghua/instruction-tuning-for-open-world-ie","repo_kind":"official","path":"processed_pretrained_data/augment_utils.py","file_url":"https://github.com/lukeming-tsinghua/instruction-tuning-for-open-world-ie/blob/HEAD/processed_pretrained_data/augment_utils.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"38cb4bd179a0bf91"}},{"code_sha256_prefix":"ba169667bd0928d0","entry":"transform","repo":"lukeming-tsinghua/instruction-tuning-for-open-world-ie","repo_kind":"official","path":"processed_pretrained_data/preprocess_func.py","file_url":"https://github.com/lukeming-tsinghua/instruction-tuning-for-open-world-ie/blob/HEAD/processed_pretrained_data/preprocess_func.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"ba169667bd0928d0"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}