{"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/inductive-relation-prediction-on-knowledge","title":"Inductive Relation Prediction by Subgraph Reasoning","arxiv_id":"1911.06962","date":"2019-11-16","proceeding":"ICML 2020 1","authors":["Komal K. Teru","Etienne Denis","William L. Hamilton"],"abstract":"The dominant paradigm for relation prediction in knowledge graphs involves learning and operating on latent representations (i.e., embeddings) of entities and relations. However, these embedding-based methods do not explicitly capture the compositional logical rules underlying the knowledge graph, and they are limited to the transductive setting, where the full set of entities must be known during training. Here, we propose a graph neural network based relation prediction framework, GraIL, that reasons over local subgraph structures and has a strong inductive bias to learn entity-independent relational semantics. Unlike embedding-based models, GraIL is naturally inductive and can generalize to unseen entities and graphs after training. We provide theoretical proof and strong empirical evidence that GraIL can represent a useful subset of first-order logic and show that GraIL outperforms existing rule-induction baselines in the inductive setting. We also demonstrate significant gains obtained by ensembling GraIL with various knowledge graph embedding methods in the transductive setting, highlighting the complementary inductive bias of our method.","url_abs":"https://arxiv.org/abs/1911.06962v2","url_pdf":"https://arxiv.org/pdf/1911.06962v2.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":"inductive-relation-prediction-on-knowledge","repo_url":"https://github.com/kkteru/grail","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"inductive-relation-prediction-on-knowledge","repo_url":"https://github.com/automl-research/red-gnn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"inductive-relation-prediction-on-knowledge","repo_url":"https://github.com/canlinzhang/siailp","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"inductive-relation-prediction-on-knowledge","repo_url":"https://github.com/jaemuzzin/plagnn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"inductive-relation-prediction-on-knowledge","repo_url":"https://github.com/lars-research/red-gnn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"inductive-relation-prediction-on-knowledge","repo_url":"https://github.com/migalkin/NodePiece","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"inductive-relation-prediction-on-knowledge","repo_url":"https://github.com/migalkin/NodePiece/tree/main/ogb","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"inductive-relation-prediction-on-knowledge","repo_url":"https://github.com/tgebhart/sheaf_kg_transind","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"inductive-relation-prediction-on-knowledge","repo_url":"https://github.com/woodcutter1998/ogb-grail-mod","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"inductive-relation-prediction-on-knowledge","repo_url":"https://github.com/zjukg/morse","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"graph-embedding","task_name":"Graph Embedding"},{"task_slug":"graph-neural-network","task_name":"Graph Neural Network"},{"task_slug":"inductive-bias","task_name":"Inductive Bias"},{"task_slug":"inductive-relation-prediction","task_name":"Inductive Relation Prediction"},{"task_slug":"inductive-knowledge-graph-completion","task_name":"Inductive knowledge graph completion"},{"task_slug":"knowledge-graph-completion","task_name":"Knowledge Graph Completion"},{"task_slug":"knowledge-graph-embedding","task_name":"Knowledge Graph Embedding"},{"task_slug":"knowledge-graphs","task_name":"Knowledge Graphs"},{"task_slug":"prediction","task_name":"Prediction"},{"task_slug":"question-answering","task_name":"Question Answering"},{"task_slug":null,"task_name":"Relation"},{"task_slug":"relation-prediction","task_name":"Relation Prediction"},{"task_slug":"relational-reasoning","task_name":"Relational Reasoning"}],"methods":[{"method_slug":"graph-neural-network","method_name":"Graph Neural Network"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1911.06962","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1911.06962"}},"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/kkteru/grail","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/woodcutter1998/ogb-grail-mod","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/automl-research/red-gnn","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/migalkin/NodePiece/tree/main/ogb","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/canlinzhang/siailp","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/tgebhart/sheaf_kg_transind","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/zjukg/morse","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/migalkin/NodePiece","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/jaemuzzin/plagnn","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/lars-research/red-gnn","reach":{"status":"ok"}}],"summary":{"ran_draft_wrong":1},"by_repo_kind":{"listed":{"samples":1,"ran":1,"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":1,"samples":[{"code_sha256_prefix":"37324da4764c0bf9","entry":"get_kge_embeddings","repo":"jaemuzzin/plagnn","repo_kind":"listed","path":"subgraph_extraction/datasets.py","file_url":"https://github.com/jaemuzzin/plagnn/blob/HEAD/subgraph_extraction/datasets.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"37324da4764c0bf9"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}