{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:3UWW4JL6GCOCI7I7B7ECWJMSF2","short_pith_number":"pith:3UWW4JL6","canonical_record":{"source":{"id":"1708.04358","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-08-14T23:52:02Z","cross_cats_sorted":["cs.IR","cs.SI"],"title_canon_sha256":"bf0c60617a223039c9c142ab7525fb71b5353a0b545e01b6f1d2eaeb57c5b90f","abstract_canon_sha256":"f42f51b48ac7b2e1c09a219ddcd29678ba15ac5f98290cfb438c1ec4b2136ae9"},"schema_version":"1.0"},"canonical_sha256":"dd2d6e257e309c247d1f0fc82b25922e91a34eadb379dde8fef2f4d44e0f58ba","source":{"kind":"arxiv","id":"1708.04358","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.04358","created_at":"2026-05-18T00:37:59Z"},{"alias_kind":"arxiv_version","alias_value":"1708.04358v1","created_at":"2026-05-18T00:37:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.04358","created_at":"2026-05-18T00:37:59Z"},{"alias_kind":"pith_short_12","alias_value":"3UWW4JL6GCOC","created_at":"2026-05-18T12:30:58Z"},{"alias_kind":"pith_short_16","alias_value":"3UWW4JL6GCOCI7I7","created_at":"2026-05-18T12:30:58Z"},{"alias_kind":"pith_short_8","alias_value":"3UWW4JL6","created_at":"2026-05-18T12:30:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:3UWW4JL6GCOCI7I7B7ECWJMSF2","target":"record","payload":{"canonical_record":{"source":{"id":"1708.04358","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-08-14T23:52:02Z","cross_cats_sorted":["cs.IR","cs.SI"],"title_canon_sha256":"bf0c60617a223039c9c142ab7525fb71b5353a0b545e01b6f1d2eaeb57c5b90f","abstract_canon_sha256":"f42f51b48ac7b2e1c09a219ddcd29678ba15ac5f98290cfb438c1ec4b2136ae9"},"schema_version":"1.0"},"canonical_sha256":"dd2d6e257e309c247d1f0fc82b25922e91a34eadb379dde8fef2f4d44e0f58ba","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:37:59.554585Z","signature_b64":"I+YEnSFVENOhOzD+OmJMaqyTUwpqIq4EF6zrg/smFGMMQi0TazhifBmD6wFhGmXKSWShW/SH2TW6rw0PP5IhBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dd2d6e257e309c247d1f0fc82b25922e91a34eadb379dde8fef2f4d44e0f58ba","last_reissued_at":"2026-05-18T00:37:59.553998Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:37:59.553998Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1708.04358","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:37:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X+Dsy0Fwr8TxiymADDrzOHu9LHq8uxC7ZzxqVTPquqi39o7nxSspvm8hxtQDfrJnyjeaVLpoMcP1tG4vwNcUCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T02:30:32.495906Z"},"content_sha256":"33472b8874a43b1a6a397f560285d32ecccc96f4e76226ddc4a936db3fc35d23","schema_version":"1.0","event_id":"sha256:33472b8874a43b1a6a397f560285d32ecccc96f4e76226ddc4a936db3fc35d23"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:3UWW4JL6GCOCI7I7B7ECWJMSF2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Continuous Representation of Location for Geolocation and Lexical Dialectology using Mixture Density Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR","cs.SI"],"primary_cat":"cs.CL","authors_text":"Afshin Rahimi, Timothy Baldwin, Trevor Cohn","submitted_at":"2017-08-14T23:52:02Z","abstract_excerpt":"We propose a method for embedding two-dimensional locations in a continuous vector space using a neural network-based model incorporating mixtures of Gaussian distributions, presenting two model variants for text-based geolocation and lexical dialectology. Evaluated over Twitter data, the proposed model outperforms conventional regression-based geolocation and provides a better estimate of uncertainty. We also show the effectiveness of the representation for predicting words from location in lexical dialectology, and evaluate it using the DARE dataset."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.04358","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":""},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:37:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sg38/n5e7uNf21Qz5rl/OHu4DbL6/dvBziY1a/Cc4w4n40nFMTSi/o0+HToB5xTiUvWW9OVQHJwjsN1y5QzuAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T02:30:32.496251Z"},"content_sha256":"4b5b95456aed16d58db6493f9b0f8c35de3544b9ff918fd60b845ed15b79fb2c","schema_version":"1.0","event_id":"sha256:4b5b95456aed16d58db6493f9b0f8c35de3544b9ff918fd60b845ed15b79fb2c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3UWW4JL6GCOCI7I7B7ECWJMSF2/bundle.json","state_url":"https://pith.science/pith/3UWW4JL6GCOCI7I7B7ECWJMSF2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3UWW4JL6GCOCI7I7B7ECWJMSF2/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-02T02:30:32Z","links":{"resolver":"https://pith.science/pith/3UWW4JL6GCOCI7I7B7ECWJMSF2","bundle":"https://pith.science/pith/3UWW4JL6GCOCI7I7B7ECWJMSF2/bundle.json","state":"https://pith.science/pith/3UWW4JL6GCOCI7I7B7ECWJMSF2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3UWW4JL6GCOCI7I7B7ECWJMSF2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:3UWW4JL6GCOCI7I7B7ECWJMSF2","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"f42f51b48ac7b2e1c09a219ddcd29678ba15ac5f98290cfb438c1ec4b2136ae9","cross_cats_sorted":["cs.IR","cs.SI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-08-14T23:52:02Z","title_canon_sha256":"bf0c60617a223039c9c142ab7525fb71b5353a0b545e01b6f1d2eaeb57c5b90f"},"schema_version":"1.0","source":{"id":"1708.04358","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.04358","created_at":"2026-05-18T00:37:59Z"},{"alias_kind":"arxiv_version","alias_value":"1708.04358v1","created_at":"2026-05-18T00:37:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.04358","created_at":"2026-05-18T00:37:59Z"},{"alias_kind":"pith_short_12","alias_value":"3UWW4JL6GCOC","created_at":"2026-05-18T12:30:58Z"},{"alias_kind":"pith_short_16","alias_value":"3UWW4JL6GCOCI7I7","created_at":"2026-05-18T12:30:58Z"},{"alias_kind":"pith_short_8","alias_value":"3UWW4JL6","created_at":"2026-05-18T12:30:58Z"}],"graph_snapshots":[{"event_id":"sha256:4b5b95456aed16d58db6493f9b0f8c35de3544b9ff918fd60b845ed15b79fb2c","target":"graph","created_at":"2026-05-18T00:37:59Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"We propose a method for embedding two-dimensional locations in a continuous vector space using a neural network-based model incorporating mixtures of Gaussian distributions, presenting two model variants for text-based geolocation and lexical dialectology. Evaluated over Twitter data, the proposed model outperforms conventional regression-based geolocation and provides a better estimate of uncertainty. We also show the effectiveness of the representation for predicting words from location in lexical dialectology, and evaluate it using the DARE dataset.","authors_text":"Afshin Rahimi, Timothy Baldwin, Trevor Cohn","cross_cats":["cs.IR","cs.SI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-08-14T23:52:02Z","title":"Continuous Representation of Location for Geolocation and Lexical Dialectology using Mixture Density Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.04358","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:33472b8874a43b1a6a397f560285d32ecccc96f4e76226ddc4a936db3fc35d23","target":"record","created_at":"2026-05-18T00:37:59Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"f42f51b48ac7b2e1c09a219ddcd29678ba15ac5f98290cfb438c1ec4b2136ae9","cross_cats_sorted":["cs.IR","cs.SI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-08-14T23:52:02Z","title_canon_sha256":"bf0c60617a223039c9c142ab7525fb71b5353a0b545e01b6f1d2eaeb57c5b90f"},"schema_version":"1.0","source":{"id":"1708.04358","kind":"arxiv","version":1}},"canonical_sha256":"dd2d6e257e309c247d1f0fc82b25922e91a34eadb379dde8fef2f4d44e0f58ba","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dd2d6e257e309c247d1f0fc82b25922e91a34eadb379dde8fef2f4d44e0f58ba","first_computed_at":"2026-05-18T00:37:59.553998Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:37:59.553998Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"I+YEnSFVENOhOzD+OmJMaqyTUwpqIq4EF6zrg/smFGMMQi0TazhifBmD6wFhGmXKSWShW/SH2TW6rw0PP5IhBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:37:59.554585Z","signed_message":"canonical_sha256_bytes"},"source_id":"1708.04358","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:33472b8874a43b1a6a397f560285d32ecccc96f4e76226ddc4a936db3fc35d23","sha256:4b5b95456aed16d58db6493f9b0f8c35de3544b9ff918fd60b845ed15b79fb2c"],"state_sha256":"3b9886493d34c87ac8bdf4547cf8ca34c2cb9a78ef9bdf4d1594be9ad56d696a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ugzmM/MLxNCLpCrAZZz8ZDyUUvy4AzfKv4uD/WHqkJmUXM3IaxtDZTU6niTHvSomNWwftyh7G5zipd0fDYyVAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T02:30:32.498124Z","bundle_sha256":"1888dd54d854d8860e91c694665229aa7db1e978193bdabdd3f021fa4da44353"}}