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Classify each adverbial *-ing* clause as one of: **FA** (Free Adjunct), **AVG** (Adverbial Verbal Gerund) or **AC** (Absolute Construction).\nIn your classification, adhere strictly to the following methodology:\n### **1. FA – Free Adjunct**\n- **No overt subject**, implied = main clause subject. \n → *Walking down the street, she smiled.*\n- May start with **optional subordinator** (*while, when, though, if*).\n- **Participial** form (*doing*, *having done*).\n- **Comma-separated**, loosely attached.\n- Expresses time, cause, condition, manner.\n*Test:* Removing it leaves a full main clause and same subject → **FA**.\n### **2. AVG – Adverbial Verbal Gerund**\n- **Always introduced by a preposition** (*after, before, by, on, in, with, without, despite*).\n- **Augmentor obligatory**; cannot drop it. \n → *After leaving, he went home.*\n- May have **genitive subject** (*by its being ruined*).\n- More **nominal** in character.\n- Preposition fixes its meaning.\n *Test:* If the clause is governed by a preposition and removing it breaks grammar → **AVG**.\n### **3. 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prompt_tokens (or completion_tokens + thinking_tokens fallback)" }, "truth_label_count": 318, "prediction_count": 318, "evaluated_example_count": 318, "calibration_metrics": { "available": true, "sample_count": 318, "bin_count": 10, "ece": 0.010911949685538144, "mce": 0.09999999999999987, "brier_score": 0.031670125786163524 }, "first_prompt_timestamp": "2026-04-03T12:47:18.635821Z", "last_prompt_timestamp": "2026-04-03T14:11:48.327508Z", "overall_time_seconds": 5069.691687, "overall_time_human": "1h 24m 30s", "accuracy": 0.9654088050314465, "cohen_kappa": 0.9257655822244859, "macro_precision": 0.9612069817549269, "macro_recall": 0.9650205761316872, "macro_f1": 0.9627218968280554, "per_label": { "AC": { "precision": 0.9545454545454546, "recall": 1.0, "f1": 0.9767441860465117, "support": 21 }, "AVG": { "precision": 0.961038961038961, "recall": 0.9135802469135802, "f1": 0.9367088607594937, "support": 81 }, "FA": { "precision": 0.9680365296803652, "recall": 0.9814814814814815, "f1": 0.9747126436781608, "support": 216 } }, "labels": [ "AC", "AVG", "FA" ], "label_count": 3, "total_examples": 318, "confusion_matrix": { "AC": { "AC": 21, "AVG": 0, "FA": 0 }, "AVG": { "AC": 0, "AVG": 74, "FA": 7 }, "FA": { "AC": 1, "AVG": 3, "FA": 212 } }, "label_metrics_available": true }