fix: use correct object types to fix all errors

croissant_metadata.json

@@ -1,6 +1,7 @@
 {
   "@context": {
     "@vocab": "https://schema.org/",
+    "@language": "en",
     "cr": "http://mlcommons.org/croissant/",
     "rai": "http://mlcommons.org/croissant/RAI/",
     "sc": "https://schema.org/"
@@ -16,6 +17,7 @@
   "url": "https://huggingface.co/datasets/themechanism/script-fidelity-benchmark",
   "version": "1.0",
   "datePublished": "2026-04-29",
+  "citation": "Anonymous. Script collapse in multilingual ASR: A reference-free metric and 100-pair benchmark. NeurIPS 2026 Evaluations and Datasets submission, 2026.",
   "creator": {
     "@type": "Organization",
     "name": "Anonymous Artifact Maintainers"
@@ -29,81 +31,92 @@
   ],
   "distribution": [
     {
-      "@type": "cr:FileObject",
-      "name": "analysis/sf_results.csv",
+      "@type": "sc:FileObject",
+      "name": "analysis_sf_results_csv",
       "contentUrl": "analysis/sf_results.csv",
       "encodingFormat": "text/csv",
-      "description": "Evaluation rows with WER, CER, SFR, and dominant-script counts. The paper's 100-pair matrix is the subset with family in Whisper, MMS, SeamlessM4T, or Gemma4; six family=unknown Pashto rows are supplemental comparisons."
+      "description": "Evaluation rows with WER, CER, SFR, and dominant-script counts. The paper's 100-pair matrix is the subset with family in Whisper, MMS, SeamlessM4T, or Gemma4; six family=unknown Pashto rows are supplemental comparisons.",
+      "sha256": "f208fcdd6ab0e7969772456a2905d10100f4801aa3abdf19e232980dd55dca53"
     },
     {
-      "@type": "cr:FileObject",
-      "name": "results_gemma4/sf_results.csv",
+      "@type": "sc:FileObject",
+      "name": "results_gemma4_sf_results_csv",
       "contentUrl": "results_gemma4/sf_results.csv",
       "encodingFormat": "text/csv",
-      "description": "Gemma 4 E2B result rows before merging into the main CSV."
+      "description": "Gemma 4 E2B result rows before merging into the main CSV.",
+      "sha256": "ce523ad936dad1187872e10b0028fef0d394c6c676123b9383b7bfef4dd865a7"
     },
     {
-      "@type": "cr:FileObject",
-      "name": "analysis/gemma4_prompt_mitigation_summary.csv",
+      "@type": "sc:FileObject",
+      "name": "analysis_gemma4_prompt_mitigation_summary_csv",
       "contentUrl": "analysis/gemma4_prompt_mitigation_summary.csv",
       "encodingFormat": "text/csv",
-      "description": "Paired Gemma 4 baseline versus script-aware prompting summary for ten FLEURS languages."
+      "description": "Paired Gemma 4 baseline versus script-aware prompting summary for ten FLEURS languages.",
+      "sha256": "5c808ea7f2afec7c07ae93d66becfad64934a7b0f615e1e84beeb9cab5bd2735"
     },
     {
-      "@type": "cr:FileObject",
-      "name": "analysis/gemma4_downstream_mt_summary.csv",
+      "@type": "sc:FileObject",
+      "name": "analysis_gemma4_downstream_mt_summary_csv",
       "contentUrl": "analysis/gemma4_downstream_mt_summary.csv",
       "encodingFormat": "text/csv",
-      "description": "Downstream NLLB translation summary comparing gold-transcript, baseline-ASR, and script-aware-ASR inputs against English FLEURS references."
+      "description": "Downstream NLLB translation summary comparing gold-transcript, baseline-ASR, and script-aware-ASR inputs against English FLEURS references.",
+      "sha256": "caf94a935b4442f6ec55bd74a22711fe89fcea4daaa7e7836e964c9f524148f8"
     },
     {
-      "@type": "cr:FileObject",
-      "name": "analysis/gemma4_downstream_mt_utterances.csv",
+      "@type": "sc:FileObject",
+      "name": "analysis_gemma4_downstream_mt_utterances_csv",
       "contentUrl": "analysis/gemma4_downstream_mt_utterances.csv",
       "encodingFormat": "text/csv",
-      "description": "Per-utterance downstream MT validation rows with English references, ASR inputs, translations, SFR, and chrF scores."
+      "description": "Per-utterance downstream MT validation rows with English references, ASR inputs, translations, SFR, and chrF scores.",
+      "sha256": "159b8a054029404222f0a1a558c55bfd640c4901405d6e4514090973de5386e9"
     },
     {
-      "@type": "cr:FileObject",
-      "name": "analysis/sfr_lid_hybrid_summary.csv",
+      "@type": "sc:FileObject",
+      "name": "analysis_sfr_lid_hybrid_summary_csv",
       "contentUrl": "analysis/sfr_lid_hybrid_summary.csv",
       "encodingFormat": "text/csv",
-      "description": "SFR plus language-identification summary over saved Gemma 4 predictions."
+      "description": "SFR plus language-identification summary over saved Gemma 4 predictions.",
+      "sha256": "6a5dbe7ec6a99e2e5c68e1dfbaee4ada512563596e6a671f7798f1e09ccfe95f"
     },
     {
-      "@type": "cr:FileObject",
-      "name": "scripts/script_fidelity.py",
+      "@type": "sc:FileObject",
+      "name": "scripts_script_fidelity_py",
       "contentUrl": "scripts/script_fidelity.py",
       "encodingFormat": "text/x-python",
-      "description": "Standalone Script Fidelity Rate implementation."
+      "description": "Standalone Script Fidelity Rate implementation.",
+      "sha256": "46239753dfcfba2792227f8bde77962f2c6bb56abed9823ab027e40b41dee238"
     },
     {
-      "@type": "cr:FileObject",
-      "name": "scripts/eval_multilang.py",
+      "@type": "sc:FileObject",
+      "name": "scripts_eval_multilang_py",
       "contentUrl": "scripts/eval_multilang.py",
       "encodingFormat": "text/x-python",
-      "description": "Evaluation driver used to generate ASR predictions and metrics."
+      "description": "Evaluation driver used to generate ASR predictions and metrics.",
+      "sha256": "e4a1e4498024340a6864c29992e41b48a4a71656bd42b2945fef95c029c9e0ee"
     },
     {
-      "@type": "cr:FileObject",
-      "name": "scripts/eval_gemma4_prompt_mitigation.py",
+      "@type": "sc:FileObject",
+      "name": "scripts_eval_gemma4_prompt_mitigation_py",
       "contentUrl": "scripts/eval_gemma4_prompt_mitigation.py",
       "encodingFormat": "text/x-python",
-      "description": "Gemma 4 script-aware prompting evaluation script."
+      "description": "Gemma 4 script-aware prompting evaluation script.",
+      "sha256": "93c6b690870bfc2ea193d552626f052253d0c722fc1d42aa3022d4f536b3bd79"
     },
     {
-      "@type": "cr:FileObject",
-      "name": "scripts/eval_downstream_mt.py",
+      "@type": "sc:FileObject",
+      "name": "scripts_eval_downstream_mt_py",
       "contentUrl": "scripts/eval_downstream_mt.py",
       "encodingFormat": "text/x-python",
-      "description": "Downstream MT validation script using English FLEURS references."
+      "description": "Downstream MT validation script using English FLEURS references.",
+      "sha256": "b1970f3d874fbcffd3528e9f43dd6800c2d2e3fbd9a92b67493eb72c60d29b7f"
     },
     {
-      "@type": "cr:FileObject",
-      "name": "scripts/eval_sfr_lid_hybrid.py",
+      "@type": "sc:FileObject",
+      "name": "scripts_eval_sfr_lid_hybrid_py",
       "contentUrl": "scripts/eval_sfr_lid_hybrid.py",
       "encodingFormat": "text/x-python",
-      "description": "SFR plus language-identification audit script for saved predictions."
+      "description": "SFR plus language-identification audit script for saved predictions.",
+      "sha256": "f4d16f883b3fbfded284872ce4e6b58c53ab76672dab3059e59ef4182bfaac99"
     }
   ],
   "cr:recordSet": [