Add filtering from known disinformation sources

agent/package-lock.json

@@ -21,6 +21,7 @@
         "fs": "^0.0.1-security",
         "langchain": "^1.2.14",
         "selenium-webdriver": "^4.40.0",
+        "tldts": "^7.0.23",
         "wink-bm25-text-search": "^3.1.2",
         "wink-nlp-utils": "^2.1.0",
         "winston": "^3.19.0"
@@ -2681,9 +2682,9 @@
       }
     },
     "node_modules/tar": {
-      "version": "7.5.7",
-      "resolved": "https://registry.npmjs.org/tar/-/tar-7.5.7.tgz",
-      "integrity": "sha512-fov56fJiRuThVFXD6o6/Q354S7pnWMJIVlDBYijsTNx6jKSE4pvrDTs6lUnmGvNyfJwFQQwWy3owKz1ucIhveQ==",
+      "version": "7.5.9",
+      "resolved": "https://registry.npmjs.org/tar/-/tar-7.5.9.tgz",
+      "integrity": "sha512-BTLcK0xsDh2+PUe9F6c2TlRp4zOOBMTkoQHQIWSIzI0R7KG46uEwq4OPk2W7bZcprBMsuaeFsqwYr7pjh6CuHg==",
       "license": "BlueOak-1.0.0",
       "dependencies": {
         "@isaacs/fs-minipass": "^4.0.0",
@@ -2702,6 +2703,24 @@
       "integrity": "sha512-uuVGNWzgJ4yhRaNSiubPY7OjISw4sw4E5Uv0wbjp+OzcbmVU/rsT8ujgcXJhn9ypzsgr5vlzpPqP+MBBKcGvbg==",
       "license": "MIT"
     },
+    "node_modules/tldts": {
+      "version": "7.0.23",
+      "resolved": "https://registry.npmjs.org/tldts/-/tldts-7.0.23.tgz",
+      "integrity": "sha512-ASdhgQIBSay0R/eXggAkQ53G4nTJqTXqC2kbaBbdDwM7SkjyZyO0OaaN1/FH7U/yCeqOHDwFO5j8+Os/IS1dXw==",
+      "license": "MIT",
+      "dependencies": {
+        "tldts-core": "^7.0.23"
+      },
+      "bin": {
+        "tldts": "bin/cli.js"
+      }
+    },
+    "node_modules/tldts-core": {
+      "version": "7.0.23",
+      "resolved": "https://registry.npmjs.org/tldts-core/-/tldts-core-7.0.23.tgz",
+      "integrity": "sha512-0g9vrtDQLrNIiCj22HSe9d4mLVG3g5ph5DZ8zCKBr4OtrspmNB6ss7hVyzArAeE88ceZocIEGkyW1Ime7fxPtQ==",
+      "license": "MIT"
+    },
     "node_modules/tmp": {
       "version": "0.2.5",
       "resolved": "https://registry.npmjs.org/tmp/-/tmp-0.2.5.tgz",

agent/package.json

@@ -25,6 +25,7 @@
     "fs": "^0.0.1-security",
     "langchain": "^1.2.14",
     "selenium-webdriver": "^4.40.0",
+    "tldts": "^7.0.23",
     "wink-bm25-text-search": "^3.1.2",
     "wink-nlp-utils": "^2.1.0",
     "winston": "^3.19.0"

agent/tools/checkDisinfo.ts

@@ -0,0 +1,55 @@
+import path from "path";
+import { logger } from "../utils/logger"
+import fs from "fs";
+import { parse } from "tldts";
+
+type RawSiteRecord = {
+    Domain: string;
+    Score: string;
+};
+
+type SiteScore = {
+    domain: string;
+    score: number;
+};
+
+const FILE_PATH = "../data/Iffy.json"
+
+function parseSiteScores(): SiteScore[] {
+    const raw = fs.readFileSync(path.resolve(FILE_PATH), "utf-8");
+    const data: unknown = JSON.parse(raw);
+
+    if (!Array.isArray(data)) {
+        throw new Error("Invalid JSON: expected array");
+    }
+
+  return data.map((item) => {
+    const record = item as RawSiteRecord;
+
+    return {
+      domain: record.Domain,
+      score: Number(record.Score),
+    };
+  });
+}
+
+let scores: SiteScore[] | null = null
+
+export function checkDisinfo(url: string): boolean {
+    if (scores == null) {
+        scores = parseSiteScores();
+    }
+
+    const domain = parse(url).domain;
+
+    const match = scores.find(itm => itm.domain == domain)
+    if (match != null) {
+        logger.warn("Bad source %s detected with score %s", url, match.score)
+        return true;
+    }
+
+    return false;
+}
+
+
+// console.log(checkDisinfo("http://www.zerohedge.com"))

agent/tools/webSearch.ts

@@ -1,4 +1,5 @@
 import axios from "axios";
+import { checkDisinfo } from "./checkDisinfo";
 
 export async function queryScraper(query: string): Promise<string[]> {
     const instance = process.env.SCRAPER_INSTANCE;
@@ -44,6 +45,10 @@ export async function queryScraper(query: string): Promise<string[]> {
     const context = data.web ?? [];
 
     const lines: string[] = context.map((item: any) => {
+        if (checkDisinfo(item.url)) {
+            return "";
+        }
+
         const title = (item.title ?? "").trim();
         const desc = (item.description ?? "").trim();
         const link = (item.url ?? "").trim();

supporting/dbkf/fetch.py

@@ -11,16 +11,16 @@ BASE_URL = "https://dbkf.ontotext.com/rest-api/search/documents"
 
 DEFAULT_PARAMS = {
     "concept": "http://weverify.eu/resource/Concept/Q212",
-    "documentTypes": "http://schema.org/Claim",
+    # "documentTypes": "http://schema.org/Claim",
     "from": "2000-01-01",
-    "to": "2026-10-17",
+    "to": "2026-02-19",
     "lang": "en",
-    "limit": 300,  # Max per page
+    "limit": 5000,  # Max per page
     "page": 1,
     "orderBy": "date"
 }
 
-NUM_RANDOM_CLAIMS = 10
+NUM_RANDOM_CLAIMS = 20
 
 OUTPUT_FILE = "../../data/claims.json"
 

supporting/scorer/display.py

@@ -1,3 +1,4 @@
+import copy
 import streamlit as st
 import json
 import random
@@ -154,6 +155,7 @@ elif view == "Single Claim Random":
         claims = bundle["claims"]
 
         st.subheader(entry.get("text"))
+        st.write(entry.get("normalized", ""))
 
         # --------------------------
         # Stable Drag IDs (FIX)
@@ -267,7 +269,7 @@ elif view == "Single Claim Random":
                 claim_obj["human_score"] = round(score, 3)
 
             save_data(INPUT_FILE, st.session_state.data)
-            save_data_clean(OUTPUT_FILE, st.session_state.data)
+            save_data_clean(OUTPUT_FILE, copy.deepcopy(st.session_state.data))
 
 
             print("Ranking converted to scores and saved!")