properly skip filters if not passed in, refactor logic

bordirlines.py

@@ -60,8 +60,7 @@ SUPPORTED_LANGUAGES = [
 SYSTEMS = ["openai", "m3"]
 MODES = ["qlang", "qlang_en", "en", "rel_langs"]
 RELEVANCE_FILTERS = ["all", "relevant", "non-relevant"]
-# # get combination of systems and supported modes
-# SUPPORTED_SOURCES = [f"{system}.{mode}" for system in SYSTEMS for mode in MODES]
+LLM_MODES = ["zeroshot", "fewshot"]
 
 ROOT_DIR = "data"
 
@@ -119,7 +118,8 @@ class BordIRLinesDataset(datasets.GeneratorBasedBuilder):
         self.relevance_filter = relevance_filter
         assert self.relevance_filter in RELEVANCE_FILTERS
         self.annotation_type = annotation_type
-        self.llm_mode = llm_mode  # Default to "fewshot"
+        self.llm_mode = llm_mode
+        assert self.llm_mode in LLM_MODES
         self.viewpoint_filter = viewpoint_filter  # Filter for a specific viewpoint
 
     def _info(self):
@@ -136,10 +136,10 @@ class BordIRLinesDataset(datasets.GeneratorBasedBuilder):
                     "doc_id": datasets.Value("string"),
                     "doc_text": datasets.Value("string"),
                     "doc_lang": datasets.Value("string"),
+                    "viewpoint_human": datasets.Value("string"),
+                    "viewpoint_llm": datasets.Value("string"),
                     "relevant_human": datasets.Value("bool"),
-                    "viewpoint": datasets.Value("string"),
-                    "relevant_llm_zeroshot": datasets.Value("bool"),
-                    "relevant_llm_fewshot": datasets.Value("bool"),
+                    "relevant_llm": datasets.Value("bool"),
                 }
             ),
         )
@@ -185,6 +185,38 @@ class BordIRLinesDataset(datasets.GeneratorBasedBuilder):
 
         return splits
 
+    def _skip_viewpoint(self, viewpoint_human, viewpoint_llm, query_entry):
+        viewpoint = get_label(viewpoint_human, viewpoint_llm, self.annotation_type)
+        if viewpoint is None:
+            return True
+
+        if self.viewpoint_filter == "Non-controllers":
+            controller = query_entry["Controller"]
+            if controller == "Unknown":
+                return True
+
+            claimants = copy(query_entry["Claimants"])
+            claimants.remove(controller)
+            return (
+                not claimants or viewpoint not in claimants
+            )  # skip if not a non-controller viewpoint
+
+        # otherwise, handle the case where we want to filter for a specific viewpoint
+        target_viewpoint = (
+            query_entry["Controller"]
+            if self.viewpoint_filter == "Controller"
+            else self.viewpoint_filter
+        )
+
+        return target_viewpoint and viewpoint != target_viewpoint
+
+    def _skip_relevance(self, relevant_human, relevant_llm):
+        # Filtering logic based on relevance preference
+        relevant = get_label(relevant_human, relevant_llm, self.annotation_type)
+        target_relevant = {"relevant": True, "non-relevant": False}.get(self.relevance_filter, None)
+        return target_relevant is not None and relevant != target_relevant
+        # If "all", do not filter anything
+
     def _generate_examples(
         self, hits_path, docs_path, queries_path, human_annotations_path, llm_annotations_path
     ):
@@ -226,54 +258,21 @@ class BordIRLinesDataset(datasets.GeneratorBasedBuilder):
 
             # Get LLM Data
             llm_data = llm_map.get((query_id, doc_id), {})
-            relevant_llm = (
-                llm_data["relevant_fewshot"]
-                if self.llm_mode == "fewshot"
-                else llm_data["relevant_zeroshot"]
-            )
-            viewpoint_llm = (
-                llm_data["territory_fewshot"]
-                if self.llm_mode == "fewshot"
-                else llm_data["territory_zeroshot"]
-            )
-
+            relevant_llm = llm_data[f"relevant_{self.llm_mode}"]
+            viewpoint_llm = llm_data[f"territory_{self.llm_mode}"]
             # Filtering logic based on viewpoint preference
             viewpoint_llm = viewpoint_llm.split(") ", 1)[-1] if not pd.isna(viewpoint_llm) else None
 
-            viewpoint = get_label(viewpoint_human, viewpoint_llm, self.annotation_type)
-            if viewpoint is None:
-                continue
-
-            if self.viewpoint_filter == "Non-controllers":
-                controller = query_entry["Controller"]
-                if controller == "Unknown":
-                    continue
-                claimants = copy(query_entry["Claimants"])
-                claimants.remove(controller)
-                if not len(claimants) or viewpoint not in claimants:
-                    continue
-            else:
-                if self.viewpoint_filter == "Controller":
-                    controller = query_entry["Controller"]
-                    target_viewpoint = controller
-                else:
-                    target_viewpoint = self.viewpoint_filter
-
-                if target_viewpoint and viewpoint != target_viewpoint:
+            if self.viewpoint_filter:
+                do_skip = self._skip_viewpoint(viewpoint_human, viewpoint_llm, query_entry)
+                if do_skip:
                     continue
 
-            # Filtering logic based on relevance preference
-            relevant = get_label(relevant_human, relevant_llm, self.annotation_type)
-            if self.relevance_filter == "relevant":
-                if not relevant:
+            if self.relevance_filter != "all":
+                do_skip = self._skip_relevance(relevant_human, relevant_llm)
+                if do_skip:
                     continue
 
-            elif self.relevance_filter == "non-relevant":
-                if relevant:
-                    continue
-
-            # If "all", do not filter anything
-
             yield (
                 counter,
                 {
@@ -286,10 +285,10 @@ class BordIRLinesDataset(datasets.GeneratorBasedBuilder):
                     "doc_id": doc_id,
                     "doc_text": docs[doc_lang][doc_id],
                     "doc_lang": doc_lang,
+                    "viewpoint_human": viewpoint_human,
+                    "viewpoint_llm": viewpoint_llm,
                     "relevant_human": relevant_human,
-                    "viewpoint": viewpoint,
-                    "relevant_llm_zeroshot": llm_data["relevant_zeroshot"],
-                    "relevant_llm_fewshot": llm_data["relevant_fewshot"],
+                    "relevant_llm": relevant_llm,
                 },
             )
             counter += 1