{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:UA5LNOTNN6VQSLXCUJNP4FQUKX","short_pith_number":"pith:UA5LNOTN","canonical_record":{"source":{"id":"2403.02078","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-04T14:24:47Z","cross_cats_sorted":[],"title_canon_sha256":"d06b96f6e624d80a1fa752ece689e855bbf837b5733f632028d5302708f09b5f","abstract_canon_sha256":"a50343077ee3f7a8b41fb38301b64939781383670deb85ff25049536c8789326"},"schema_version":"1.0"},"canonical_sha256":"a03ab6ba6d6fab092ee2a25afe161455f75bb89d5ad38b0f94adab713c66a477","source":{"kind":"arxiv","id":"2403.02078","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.02078","created_at":"2026-07-05T07:51:56Z"},{"alias_kind":"arxiv_version","alias_value":"2403.02078v1","created_at":"2026-07-05T07:51:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.02078","created_at":"2026-07-05T07:51:56Z"},{"alias_kind":"pith_short_12","alias_value":"UA5LNOTNN6VQ","created_at":"2026-07-05T07:51:56Z"},{"alias_kind":"pith_short_16","alias_value":"UA5LNOTNN6VQSLXC","created_at":"2026-07-05T07:51:56Z"},{"alias_kind":"pith_short_8","alias_value":"UA5LNOTN","created_at":"2026-07-05T07:51:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:UA5LNOTNN6VQSLXCUJNP4FQUKX","target":"record","payload":{"canonical_record":{"source":{"id":"2403.02078","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-04T14:24:47Z","cross_cats_sorted":[],"title_canon_sha256":"d06b96f6e624d80a1fa752ece689e855bbf837b5733f632028d5302708f09b5f","abstract_canon_sha256":"a50343077ee3f7a8b41fb38301b64939781383670deb85ff25049536c8789326"},"schema_version":"1.0"},"canonical_sha256":"a03ab6ba6d6fab092ee2a25afe161455f75bb89d5ad38b0f94adab713c66a477","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:51:56.114739Z","signature_b64":"blrOP7iTWGSPSMHVAJ/EaGily3lJ0ukmIhybLYJKHX3Ryu8Q96+V5wXmgDjsRLEdceLOR4XTi5A8T+A+VwEtBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a03ab6ba6d6fab092ee2a25afe161455f75bb89d5ad38b0f94adab713c66a477","last_reissued_at":"2026-07-05T07:51:56.114382Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:51:56.114382Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.02078","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":"2026-07-05T07:51:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dsvCRtaxzpmHsL5ZJPoS3KjwJjD8249xUI/OT/ZR2Xc0D9T8tWxRT8RPwsF+PNtYr3EYInHa5oz6IYx/OF7XDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T19:30:42.547985Z"},"content_sha256":"6283fb9cadae2854351346d58799b0793606cb11ba74f0ea6fd96d4e482dd02c","schema_version":"1.0","event_id":"sha256:6283fb9cadae2854351346d58799b0793606cb11ba74f0ea6fd96d4e482dd02c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:UA5LNOTNN6VQSLXCUJNP4FQUKX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Automated Generation of Multiple-Choice Cloze Questions for Assessing English Vocabulary Using GPT-turbo 3.5","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Ayaka Sugawara, Naho Orita, Qiao Wang, Ralph Rose","submitted_at":"2024-03-04T14:24:47Z","abstract_excerpt":"A common way of assessing language learners' mastery of vocabulary is via multiple-choice cloze (i.e., fill-in-the-blank) questions. But the creation of test items can be laborious for individual teachers or in large-scale language programs. In this paper, we evaluate a new method for automatically generating these types of questions using large language models (LLM). The VocaTT (vocabulary teaching and training) engine is written in Python and comprises three basic steps: pre-processing target word lists, generating sentences and candidate word options using GPT, and finally selecting suitabl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.02078","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/2403.02078/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:51:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lbhWzBewCiZGaa1twHae6m2wbuQ18D7qv0MOYEP31Rpkhjv3dfL59DdBtlTBScaOiiRyP3u88q/ZtiATnwxRAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T19:30:42.549598Z"},"content_sha256":"d5e0fa791e37b9639a88383a7419cbebb30ee4b33ebe411da6fa2ba89b496818","schema_version":"1.0","event_id":"sha256:d5e0fa791e37b9639a88383a7419cbebb30ee4b33ebe411da6fa2ba89b496818"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UA5LNOTNN6VQSLXCUJNP4FQUKX/bundle.json","state_url":"https://pith.science/pith/UA5LNOTNN6VQSLXCUJNP4FQUKX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UA5LNOTNN6VQSLXCUJNP4FQUKX/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":"2026-08-19T19:30:42Z","links":{"resolver":"https://pith.science/pith/UA5LNOTNN6VQSLXCUJNP4FQUKX","bundle":"https://pith.science/pith/UA5LNOTNN6VQSLXCUJNP4FQUKX/bundle.json","state":"https://pith.science/pith/UA5LNOTNN6VQSLXCUJNP4FQUKX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UA5LNOTNN6VQSLXCUJNP4FQUKX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:UA5LNOTNN6VQSLXCUJNP4FQUKX","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":"a50343077ee3f7a8b41fb38301b64939781383670deb85ff25049536c8789326","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-04T14:24:47Z","title_canon_sha256":"d06b96f6e624d80a1fa752ece689e855bbf837b5733f632028d5302708f09b5f"},"schema_version":"1.0","source":{"id":"2403.02078","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.02078","created_at":"2026-07-05T07:51:56Z"},{"alias_kind":"arxiv_version","alias_value":"2403.02078v1","created_at":"2026-07-05T07:51:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.02078","created_at":"2026-07-05T07:51:56Z"},{"alias_kind":"pith_short_12","alias_value":"UA5LNOTNN6VQ","created_at":"2026-07-05T07:51:56Z"},{"alias_kind":"pith_short_16","alias_value":"UA5LNOTNN6VQSLXC","created_at":"2026-07-05T07:51:56Z"},{"alias_kind":"pith_short_8","alias_value":"UA5LNOTN","created_at":"2026-07-05T07:51:56Z"}],"graph_snapshots":[{"event_id":"sha256:d5e0fa791e37b9639a88383a7419cbebb30ee4b33ebe411da6fa2ba89b496818","target":"graph","created_at":"2026-07-05T07:51:56Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2403.02078/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A common way of assessing language learners' mastery of vocabulary is via multiple-choice cloze (i.e., fill-in-the-blank) questions. But the creation of test items can be laborious for individual teachers or in large-scale language programs. In this paper, we evaluate a new method for automatically generating these types of questions using large language models (LLM). The VocaTT (vocabulary teaching and training) engine is written in Python and comprises three basic steps: pre-processing target word lists, generating sentences and candidate word options using GPT, and finally selecting suitabl","authors_text":"Ayaka Sugawara, Naho Orita, Qiao Wang, Ralph Rose","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-04T14:24:47Z","title":"Automated Generation of Multiple-Choice Cloze Questions for Assessing English Vocabulary Using GPT-turbo 3.5"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.02078","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":"sha256:6283fb9cadae2854351346d58799b0793606cb11ba74f0ea6fd96d4e482dd02c","target":"record","created_at":"2026-07-05T07:51:56Z","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":"a50343077ee3f7a8b41fb38301b64939781383670deb85ff25049536c8789326","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-04T14:24:47Z","title_canon_sha256":"d06b96f6e624d80a1fa752ece689e855bbf837b5733f632028d5302708f09b5f"},"schema_version":"1.0","source":{"id":"2403.02078","kind":"arxiv","version":1}},"canonical_sha256":"a03ab6ba6d6fab092ee2a25afe161455f75bb89d5ad38b0f94adab713c66a477","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a03ab6ba6d6fab092ee2a25afe161455f75bb89d5ad38b0f94adab713c66a477","first_computed_at":"2026-07-05T07:51:56.114382Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:51:56.114382Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"blrOP7iTWGSPSMHVAJ/EaGily3lJ0ukmIhybLYJKHX3Ryu8Q96+V5wXmgDjsRLEdceLOR4XTi5A8T+A+VwEtBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:51:56.114739Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.02078","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6283fb9cadae2854351346d58799b0793606cb11ba74f0ea6fd96d4e482dd02c","sha256:d5e0fa791e37b9639a88383a7419cbebb30ee4b33ebe411da6fa2ba89b496818"],"state_sha256":"840c5e979170eedff6f6ba3bc243373084ef66564a5ea6b309e0fbf58d05bb85"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"df83kl/BrFYniz1ClilgbLJTrODwJCXL3YdyjrjUCmFTJPNU3vX9mYRVA0mvA8Iftcx8Sde5f2S+KkXiqWA4Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T19:30:42.557208Z","bundle_sha256":"ee0dcf54f83da86dd7467f40ae9d33b0cfe880f6addc6147fdf2a2c5939e3641"}}