{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:ZF4QVYJI35VEZVZ2WBTTHIO6JY","short_pith_number":"pith:ZF4QVYJI","schema_version":"1.0","canonical_sha256":"c9790ae128df6a4cd73ab06733a1de4e27f17ee303fbae822cf0a4f5664b363a","source":{"kind":"arxiv","id":"2103.03730","version":1},"attestation_state":"computed","paper":{"title":"Parsing Indonesian Sentence into Abstract Meaning Representation using Machine Learning Approach","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Adylan Roaffa Ilmy, Masayu Leylia Khodra","submitted_at":"2021-03-05T15:01:59Z","abstract_excerpt":"Abstract Meaning Representation (AMR) provides many information of a sentence such as semantic relations, coreferences, and named entity relation in one representation. However, research on AMR parsing for Indonesian sentence is fairly limited. In this paper, we develop a system that aims to parse an Indonesian sentence using a machine learning approach. Based on Zhang et al. work, our system consists of three steps: pair prediction, label prediction, and graph construction. Pair prediction uses dependency parsing component to get the edges between the words for the AMR. The result of pair pre"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2103.03730","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2021-03-05T15:01:59Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"1aab76dafff768b1c8dcae7cc52e5bd99908d3ee53132bef8f467f0617630cc2","abstract_canon_sha256":"48947f1a22240a501ec68216bd887b07d3161471e7233f85258f8460f28e4759"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:20:39.325612Z","signature_b64":"p6wzsPb6PIZWaV3BRCu/44IbcbmAzPrEacac0udpyMMU5DjQIMZnrIekBDOzgAjSni+JDemAXgmneBscJ1SKAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c9790ae128df6a4cd73ab06733a1de4e27f17ee303fbae822cf0a4f5664b363a","last_reissued_at":"2026-07-05T02:20:39.325178Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:20:39.325178Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Parsing Indonesian Sentence into Abstract Meaning Representation using Machine Learning Approach","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Adylan Roaffa Ilmy, Masayu Leylia Khodra","submitted_at":"2021-03-05T15:01:59Z","abstract_excerpt":"Abstract Meaning Representation (AMR) provides many information of a sentence such as semantic relations, coreferences, and named entity relation in one representation. However, research on AMR parsing for Indonesian sentence is fairly limited. In this paper, we develop a system that aims to parse an Indonesian sentence using a machine learning approach. Based on Zhang et al. work, our system consists of three steps: pair prediction, label prediction, and graph construction. Pair prediction uses dependency parsing component to get the edges between the words for the AMR. The result of pair pre"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.03730","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2103.03730/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2103.03730","created_at":"2026-07-05T02:20:39.325245+00:00"},{"alias_kind":"arxiv_version","alias_value":"2103.03730v1","created_at":"2026-07-05T02:20:39.325245+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.03730","created_at":"2026-07-05T02:20:39.325245+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZF4QVYJI35VE","created_at":"2026-07-05T02:20:39.325245+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZF4QVYJI35VEZVZ2","created_at":"2026-07-05T02:20:39.325245+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZF4QVYJI","created_at":"2026-07-05T02:20:39.325245+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ZF4QVYJI35VEZVZ2WBTTHIO6JY","json":"https://pith.science/pith/ZF4QVYJI35VEZVZ2WBTTHIO6JY.json","graph_json":"https://pith.science/api/pith-number/ZF4QVYJI35VEZVZ2WBTTHIO6JY/graph.json","events_json":"https://pith.science/api/pith-number/ZF4QVYJI35VEZVZ2WBTTHIO6JY/events.json","paper":"https://pith.science/paper/ZF4QVYJI"},"agent_actions":{"view_html":"https://pith.science/pith/ZF4QVYJI35VEZVZ2WBTTHIO6JY","download_json":"https://pith.science/pith/ZF4QVYJI35VEZVZ2WBTTHIO6JY.json","view_paper":"https://pith.science/paper/ZF4QVYJI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2103.03730&json=true","fetch_graph":"https://pith.science/api/pith-number/ZF4QVYJI35VEZVZ2WBTTHIO6JY/graph.json","fetch_events":"https://pith.science/api/pith-number/ZF4QVYJI35VEZVZ2WBTTHIO6JY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZF4QVYJI35VEZVZ2WBTTHIO6JY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZF4QVYJI35VEZVZ2WBTTHIO6JY/action/storage_attestation","attest_author":"https://pith.science/pith/ZF4QVYJI35VEZVZ2WBTTHIO6JY/action/author_attestation","sign_citation":"https://pith.science/pith/ZF4QVYJI35VEZVZ2WBTTHIO6JY/action/citation_signature","submit_replication":"https://pith.science/pith/ZF4QVYJI35VEZVZ2WBTTHIO6JY/action/replication_record"}},"created_at":"2026-07-05T02:20:39.325245+00:00","updated_at":"2026-07-05T02:20:39.325245+00:00"}