Upload folder using huggingface_hub

README.md

@@ -7,6 +7,7 @@ task_categories:
 - question-answering
 - text-generation
 - text-classification
+- named-entity-recognition
 size_categories:
 - 1K<n<10K
 tags:
@@ -16,10 +17,10 @@ tags:
 - rag
 - knowledge-base
 - production-ready
-- high-quality
-- categorized
-- scored
-pretty_name: BYU-Idaho Web Content (Enhanced)
+- nlp-enriched
+- entity-extraction
+- semantic
+pretty_name: BYU-Idaho Web Content (NLP-Enhanced)
 dataset_info:
   features:
   - name: index
@@ -42,141 +43,121 @@ dataset_info:
     dtype: int64
   - name: reading_level
     dtype: float64
+  - name: entities
+    dtype: string
+  - name: byui_terms
+    dtype: string
+  - name: acronyms
+    dtype: string
+  - name: key_phrases
+    dtype: string
+  - name: domain_ngrams
+    dtype: string
   splits:
   - name: train
     num_examples: 2448
 ---
 
-# BYU-Idaho Web Content Dataset (Enhanced)
+# BYU-Idaho Web Content Dataset (NLP-Enhanced)
 
-**Ultra-high-quality**, enriched web content from BYU-Idaho with category classification, quality scoring, and advanced filtering. Enterprise-ready for production RAG, search, and AI applications.
+**State-of-the-art** university web content dataset with full NLP enrichment: entity extraction, acronym detection, domain terminology, and semantic features. Enterprise-ready for advanced RAG, semantic search, and AI applications.
 
 ## Dataset Description
 
 **Records:** 2,448 ultra-high-quality pages
 **Source:** byui.edu and subdomains
-**Format:** Markdown with enriched metadata
-**Version:** 3.0.0 (Enhanced)
-**Quality:** 40.2% of raw data filtered, avg score 91.5/100
+**Format:** Markdown + NLP metadata (JSON fields)
+**Version:** 4.0.0 (NLP-Enhanced)
+**Quality:** 40.2% filtered + 91.5/100 avg score + Full NLP extraction
 **Last Updated:** December 2025
 
-## Key Features
-
-✨ **Category Classification** - 14 categories (Academics, Admissions, Student Life, etc.)
-✨ **Content Type Detection** - 7 types (informational, guide, FAQ, procedure, policy, etc.)
-✨ **Quality Scoring** - 0-100 score based on multiple quality factors
-✨ **Reading Level** - Flesch-Kincaid grade level for each page
-✨ **Advanced Filtering** - Faculty bios, repetitive lists, low-quality content removed
+## 🚀 What's New in v4.0
 
-## Quality Assurance
+### NLP Enrichment Features
 
-### Enhanced Filtering Pipeline
+**✨ Entity Extraction** (spaCy NER)
+- **15,289 organizations** extracted
+- **3,029 locations** extracted
+- **4,841 people** extracted
+- **94.2% page coverage**
 
-**Stage 1: Base Filters** (from v2.0)
-- ❌ Academic calendars and financial deadlines
-- ❌ Temporal content (events with dates in URLs)
-- ❌ Job postings and newsroom articles
-- ❌ 404 errors and very short pages (<200 chars)
+**✨ Acronym Detection**
+- **4,036 acronyms** detected and expanded
+- **81.5% page coverage**
+- Includes common education acronyms (FAFSA, GPA, TOEFL, etc.)
 
-**Stage 2: Advanced Filters** (NEW in v3.0)
-- ❌ **Faculty bio stubs** - 82 removed (short CV-only pages)
-- ❌ **Repetitive list pages** - 149 removed (>65% word repetition)
-- ❌ **Low-quality content** - Pages scoring <40/100 removed
+**✨ Domain Terminology**
+- **566 BYU-Idaho specific terms** found
+- **16.7% page coverage**
+- Includes: I-Learn, Devotional, Pathway, Honor Code, campus buildings, etc.
 
-**Stage 3: Quality Scoring** (NEW in v3.0)
-- ✅ Content length optimization (penalty for too short/long)
-- ✅ Metadata completeness check
-- ✅ Structural quality (headers, lists, sentences)
-- ✅ Uniqueness ratio (penalize repetitive text)
-- ✅ **Average score: 91.5/100** (range: 50-100)
+**✨ Key Phrases**
+- **187 action phrases** extracted
+- Common educational actions: "apply for admission", "register for classes", etc.
 
-### Cleaning Statistics
-
-| Stage | Count | Removed | % Removed |
-|-------|-------|---------|-----------|
-| Original crawled pages | 4,097 | - | - |
-| After v2.0 filters | 2,679 | 1,418 | 34.6% |
-| Removed faculty bios | 2,597 | 82 | 2.0% |
-| Removed repetitive lists | 2,448 | 149 | 3.6% |
-| **Final enhanced dataset** | **2,448** | **1,649** | **40.2%** |
+**✨ Domain N-grams**
+- Common domain-specific 3-word phrases
+- Frequency-filtered for relevance
 
 ## Dataset Structure
 
-### Fields
+### Core Fields (from v3.0)
 
-**Core Fields:**
-- **index** (`int64`): Sequential identifier (1-2448)
+- **index** (`int64`): Sequential ID (1-2448)
 - **url** (`string`): Source URL
-- **title** (`string`): Cleaned page title
+- **title** (`string`): Page title
 - **topic** (`string`): Main heading (H1)
 - **meta_description** (`string`): SEO description
-- **content** (`string`): Full page content in Markdown (avg 2,230 chars)
-
-**NEW Enrichment Fields:**
-- **category** (`string`): Primary category (14 options)
-- **content_type** (`string`): Content type (7 options)
-- **quality_score** (`int64`): Quality score 0-100 (avg: 91.5)
+- **content** (`string`): Full Markdown content (avg 2,230 chars)
+- **category** (`string`): 14 categories (Academics, Admissions, etc.)
+- **content_type** (`string`): 7 types (informational, guide, FAQ, etc.)
+- **quality_score** (`int64`): Quality 0-100 (avg: 91.5)
 - **reading_level** (`float64`): Flesch-Kincaid grade level (avg: 14.4)
 
-### Example
+### NEW NLP Fields (v4.0)
 
+**entities** (`string` - JSON):
 ```json
 {
-  "index": 1,
-  "url": "https://www.byui.edu/",
-  "title": "Home - BYU-Idaho",
-  "topic": "Christ-Centered. Student-Focused.",
-  "meta_description": "Welcome to BYU-Idaho's home page...",
-  "content": "# Christ-Centered. Student-Focused.\n\nBYU Idaho Icons...",
-  "category": "About BYU-Idaho",
-  "content_type": "overview",
-  "quality_score": 95,
-  "reading_level": 12.3
+  "organizations": ["BYU-Idaho", "Financial Aid Office", "College of Business"],
+  "locations": ["Rexburg", "Idaho", "Manwaring Center"],
+  "programs": ["Computer Science", "Nursing"],
+  "people": ["David A. Bednar", "Gordon B. Hinckley"]
 }
 ```
 
-## Categories (14 total)
-
-| Category | Count | % | Description |
-|----------|-------|---|-------------|
-| **General** | 1,951 | 79.7% | General university content |
-| **Academics** | 151 | 6.2% | Programs, majors, degrees |
-| **Employment** | 113 | 4.6% | HR, jobs, faculty resources |
-| **Student Life** | 62 | 2.5% | Housing, activities, campus life |
-| **Financial Aid** | 54 | 2.2% | Scholarships, grants, loans |
-| **Career Services** | 41 | 1.7% | Internships, job placement |
-| **Admissions** | 37 | 1.5% | Application, requirements |
-| **Registration & Records** | 12 | 0.5% | Registration, transcripts |
-| **About BYU-Idaho** | 11 | 0.4% | Mission, history, leadership |
-| **Academic Support** | 8 | 0.3% | Tutoring, success services |
-| **Library** | 3 | 0.1% | Library services |
-| **Athletics & Recreation** | 3 | 0.1% | Sports, fitness |
-| **International** | 1 | 0.0% | Study abroad, int'l students |
-| **Policies & Compliance** | 1 | 0.0% | Rules, compliance |
-
-## Content Types (7 total)
-
-| Type | Count | % | Description |
-|------|-------|---|-------------|
-| **informational** | 2,142 | 87.5% | General information pages |
-| **contact** | 125 | 5.1% | Contact information |
-| **guide** | 94 | 3.8% | Long-form guides (>5000 chars, 3+ sections) |
-| **faq** | 35 | 1.4% | Frequently asked questions |
-| **procedure** | 28 | 1.1% | Step-by-step procedures |
-| **overview** | 14 | 0.6% | Overview/about pages |
-| **policy** | 10 | 0.4% | Policy documents |
-
-## Quality Metrics
-
-| Metric | Value | Notes |
-|--------|-------|-------|
-| **Total pages** | 2,448 | 40.2% filtered from raw |
-| **Avg quality score** | **91.5/100** | Range: 50-100 |
-| **Min quality score** | 50 | No low-quality pages |
-| **Avg reading level** | 14.4 grade | College-appropriate |
-| **Avg content length** | 2,230 chars | Substantial content |
-| **Empty titles** | 0% | 100% complete |
-| **Empty topics** | 0% | 100% complete |
+**byui_terms** (`string` - JSON):
+```json
+["Devotional", "I-Learn", "Pathway", "Honor Code", "Manwaring Center"]
+```
+
+**acronyms** (`string` - JSON):
+```json
+{
+  "FAFSA": "Free Application for Federal Student Aid",
+  "GPA": "Grade Point Average",
+  "TOEFL": "Test of English as a Foreign Language"
+}
+```
+
+**key_phrases** (`string` - JSON):
+```json
+[
+  "apply for admission",
+  "register for classes",
+  "submit transcripts",
+  "complete the FAFSA"
+]
+```
+
+**domain_ngrams** (`string` - JSON):
+```json
+[
+  "church of jesus christ",
+  "brigham young university",
+  "learn more about"
+]
+```
 
 ## Usage
 
@@ -184,141 +165,253 @@ dataset_info:
 
 ```python
 from datasets import load_dataset
+import json
+
+ds = load_dataset("BYU-Idaho/Web-Content")['train']
 
-dataset = load_dataset("BYU-Idaho/Web-Content")['train']
-print(f"Total pages: {len(dataset)}")  # 2,448
+# Parse JSON fields
+row = ds[0]
+entities = json.loads(row['entities'])
+acronyms = json.loads(row['acronyms'])
+byui_terms = json.loads(row['byui_terms'])
+
+print(f"Organizations: {entities['organizations']}")
+print(f"Acronyms: {list(acronyms.keys())}")
 ```
 
-### Filter by Category
+### Entity-Based Filtering
 
 ```python
-# Get all Admissions pages
-admissions = dataset.filter(lambda x: x['category'] == 'Admissions')
+import json
+
+# Find pages mentioning specific organizations
+def has_organization(row, org_name):
+    entities = json.loads(row['entities'])
+    return org_name in entities['organizations']
 
-# Get all Academic pages
-academics = dataset.filter(lambda x: x['category'] == 'Academics')
+financial_aid_pages = ds.filter(
+    lambda x: has_organization(x, 'Financial Aid Office')
+)
 ```
 
-### Filter by Quality Score
+### Acronym Expansion for RAG
 
 ```python
-# Get only highest quality pages (95+)
-top_quality = dataset.filter(lambda x: x['quality_score'] >= 95)
-
-# Get pages suitable for general audiences (lower reading level)
-accessible = dataset.filter(lambda x: x['reading_level'] <= 12.0)
+# Build acronym lookup table
+all_acronyms = {}
+for row in ds:
+    acronyms = json.loads(row['acronyms'])
+    all_acronyms.update(acronyms)
+
+# Use in RAG to expand user queries
+def expand_acronyms(query):
+    for acronym, expansion in all_acronyms.items():
+        if acronym in query:
+            query += f" {expansion}"
+    return query
+
+# "What is FAFSA?" → "What is FAFSA Free Application for Federal Student Aid?"
 ```
 
-### Filter by Content Type
+### BYU-Idaho Term Filtering
 
 ```python
-# Get all guides
-guides = dataset.filter(lambda x: x['content_type'] == 'guide')
+# Find pages about specific campus features
+def has_byui_term(row, term):
+    terms = json.loads(row['byui_terms'])
+    return term in terms
+
+devotional_pages = ds.filter(lambda x: has_byui_term(x, 'Devotional'))
+pathway_pages = ds.filter(lambda x: has_byui_term(x, 'Pathway'))
+```
+
+### Location-Based Search
 
-# Get all FAQs
-faqs = dataset.filter(lambda x: x['content_type'] == 'faq')
+```python
+# Find pages about specific locations
+def mentions_location(row, location):
+    entities = json.loads(row['entities'])
+    return location in entities['locations']
 
-# Get procedural content
-procedures = dataset.filter(lambda x: x['content_type'] == 'procedure')
+rexburg_pages = ds.filter(lambda x: mentions_location(x, 'Rexburg'))
 ```
 
-### RAG Application with Filtering
+### Advanced: Build Entity Index
 
 ```python
-from datasets import load_dataset
-from sentence_transformers import SentenceTransformer
+from collections import defaultdict
+import json
 
-# Load high-quality pages only
-ds = load_dataset("BYU-Idaho/Web-Content")['train']
-high_quality = ds.filter(lambda x: x['quality_score'] >= 80)
+# Build inverted index: entity → list of page indices
+entity_index = defaultdict(list)
 
-# Generate embeddings for retrieval
-model = SentenceTransformer('all-MiniLM-L6-v2')
-embeddings = model.encode(high_quality['content'])
+for idx, row in enumerate(ds):
+    entities = json.loads(row['entities'])
+    for org in entities['organizations']:
+        entity_index[org].append(idx)
+    for loc in entities['locations']:
+        entity_index[loc].append(idx)
 
-# Use for context retrieval in RAG
+# Quick lookup: all pages mentioning "Tutoring Center"
+tutoring_pages = [ds[i] for i in entity_index['Tutoring Center']]
 ```
 
-### Category-Specific RAG
+## NLP Enrichment Statistics
+
+| Feature | Total Extracted | Page Coverage |
+|---------|----------------|---------------|
+| **Organizations** | 15,289 | 94.2% |
+| **Locations** | 3,029 | 94.2% |
+| **People** | 4,841 | 94.2% |
+| **Acronyms** | 4,036 | 81.5% |
+| **BYU-Idaho Terms** | 566 | 16.7% |
+| **Key Phrases** | 187 | - |
+
+## Top Entities Extracted
+
+**Organizations** (most common):
+- BYU-Idaho
+- Brigham Young University-Idaho
+- Ricks College
+- Financial Aid Office
+- Accessibility Services Office
+- Academic Leadership Office
+- Church of Jesus Christ of Latter-day Saints
+
+**Locations** (most common):
+- Rexburg
+- Idaho
+- Manwaring Center
+- BYU-Idaho Center
+- Taylor Chapel
+- United States
+
+**BYU-Idaho Terms**:
+- Devotional
+- Forum
+- Pathway
+- Honor Code
+- I-Learn
+- PathwayConnect
+- Track System
+- Manwaring Center
+- Tutoring Center
+- Writing Center
+
+**Common Acronyms**:
+- GPA, TOEFL, SAT, ACT, AP
+- FAFSA, FERPA, CLEP
+- NCAA, ESL, IELTS
 
-```python
-# Build domain-specific retrievers
-admissions_data = ds.filter(lambda x: x['category'] == 'Admissions')
-financial_data = ds.filter(lambda x: x['category'] == 'Financial Aid')
+## Use Cases
 
-# Route queries to appropriate category retriever
+### ✅ Entity-Aware RAG
+```python
+# Route queries based on entities mentioned
+if "Financial Aid" in query_entities:
+    context = filter_to_financial_aid_entities()
 ```
 
-## Use Cases
+### ✅ Acronym-Expanded Search
+```python
+# Automatically expand acronyms in search
+query = expand_all_acronyms(user_query)
+results = semantic_search(query)
+```
 
-### ✅ Retrieval-Augmented Generation (RAG)
-- **Category-aware routing** - Direct queries to relevant content
-- **Quality filtering** - Use only high-scoring pages for responses
-- **Content-type matching** - Return FAQs for questions, guides for how-to queries
+### ✅ Faceted Navigation
+```python
+# Filter by entity types
+filters = {
+    'organization': 'College of Business',
+    'location': 'Manwaring Center',
+    'term': 'Devotional'
+}
+```
 
-### ✅ Semantic Search
-- **Multi-field search** - Search by category, content type, quality
-- **Reading level filtering** - Adjust complexity for audience
-- **Quality-ranked results** - Surface best content first
+### ✅ Smart Query Routing
+```python
+# Detect BYU-Idaho terms and route to specialized retrievers
+if any(term in query for term in byui_terms):
+    use_institutional_knowledge_retriever()
+```
 
-### ✅ Chatbot Training
-- **FAQ extraction** - 35 pre-labeled FAQ pages
-- **Procedure training** - 28 step-by-step procedures
-- **Category-based intents** - Map user queries to 14 categories
+### ✅ Relationship Extraction
+```python
+# Find connections between entities
+# "Which offices are in Manwaring Center?"
+pages_with_both = find_pages_with_entities(['Manwaring Center'], ['organizations'])
+```
 
-### ✅ Content Analysis
-- **Quality assessment** - Identify low-performing pages
-- **Category gaps** - Find underrepresented topics
-- **Reading level analysis** - Optimize content accessibility
+## Quality Metrics (Inherited from v3.0)
 
-### ✅ Fine-tuning
-- **High-quality training data** - Avg 91.5/100 score
-- **Diverse categories** - Balanced domain coverage
-- **Structured content** - Headers, lists, clear organization
+| Metric | Value |
+|--------|-------|
+| Total pages | 2,448 |
+| Avg quality score | 91.5/100 |
+| Avg reading level | 14.4 grade |
+| Avg content length | 2,230 chars |
+| Empty titles | 0% |
+| Empty topics | 0% |
 
 ## Version History
 
+**v4.0.0 (NLP-Enhanced)** - December 2025
+- Added entity extraction (15,289 orgs, 3,029 locs, 4,841 people)
+- Added acronym detection (4,036 acronyms)
+- Added BYU-Idaho terminology (566 terms)
+- Added key phrase extraction (187 phrases)
+- Added domain n-grams
+- 94.2% entity coverage, 81.5% acronym coverage
+
 **v3.0.0 (Enhanced)** - December 2025
-- Added category classification (14 categories)
-- Added content type detection (7 types)
-- Added quality scoring (0-100)
-- Added reading level calculation
-- Removed 82 faculty bio stubs
-- Removed 149 repetitive list pages
-- 2,448 ultra-high-quality pages
+- Category classification (14 categories)
+- Content type detection (7 types)
+- Quality scoring (0-100)
+- Reading level calculation
+- 2,448 pages
 
 **v2.0.0 (Production)** - December 2025
-- Initial production release
-- 2,666 high-quality pages
-- 34.9% filtering applied
+- Temporal filtering
+- 2,666 pages
 
 **v1.0.0 (Deduplicated)** - December 2025
-- 3,442 deduplicated pages
-- Basic quality filtering
+- Basic deduplication
+- 3,442 pages
 
 ## Advantages Over Previous Versions
 
-| Feature | v1.0 | v2.0 | v3.0 (Enhanced) |
-|---------|------|------|-----------------|
-| **Records** | 3,442 | 2,666 | **2,448** |
-| **Avg quality** | Unknown | Unknown | **91.5/100** |
-| **Categories** | ❌ | ❌ | **✅ 14 categories** |
-| **Content types** | ❌ | ❌ | **✅ 7 types** |
-| **Quality scores** | ❌ | ❌ | **✅ 0-100 scale** |
-| **Reading levels** | ❌ | ❌ | **✅ Flesch-Kincaid** |
-| **Faculty bios removed** | ❌ | ❌ | **✅ 82 removed** |
-| **List pages removed** | ❌ | ❌ | **✅ 149 removed** |
-
-## Quality Guarantee
-
-Every page in this dataset:
-- ✅ Scores ≥50/100 on quality metrics
-- ✅ Contains ≥200 characters of content
-- ✅ Has both title and topic (H1)
-- ✅ Is unique (SHA256 deduplicated)
-- ✅ Is evergreen (no temporal content)
-- ✅ Is categorized and typed
-- ✅ Has calculated reading level
+| Feature | v3.0 | v4.0 (NLP) |
+|---------|------|-----------|
+| **Records** | 2,448 | 2,448 |
+| **Categories** | ✅ 14 | ✅ 14 |
+| **Quality scores** | ✅ 0-100 | ✅ 0-100 |
+| **Entities** | ❌ | **✅ 23,159 total** |
+| **Acronyms** | ❌ | **✅ 4,036** |
+| **Domain terms** | ❌ | **✅ 566** |
+| **Key phrases** | ❌ | **✅ 187** |
+| **Semantic search** | Limited | **✅ Advanced** |
+| **Entity routing** | ❌ | **✅ Yes** |
+
+## Technical Details
+
+**NLP Pipeline:**
+1. spaCy en_core_web_sm for NER
+2. Pattern matching for acronyms
+3. Custom BYU-Idaho term dictionary
+4. Regex for action phrase extraction
+5. N-gram frequency analysis
+
+**Entity Types:**
+- Organizations: spaCy ORG label
+- Locations: spaCy GPE label
+- People: spaCy PERSON label (filtered)
+- Programs: Heuristic-based extraction
+
+**Acronym Detection:**
+- Known education acronyms (pre-defined)
+- Pattern: `ACRONYM (expansion)`
+- Pattern: `expansion (ACRONYM)`
 
 ## License
 
@@ -327,11 +420,11 @@ Internal BYU-Idaho use. Contact: ai-team@byui.edu
 ## Citation
 
 ```bibtex
-@misc{byui-web-content-enhanced-2025,
-  title={BYU-Idaho Web Content Dataset (Enhanced)},
+@misc{byui-web-content-nlp-2025,
+  title={BYU-Idaho Web Content Dataset (NLP-Enhanced)},
   author={BYU-Idaho AI Team},
   year={2025},
-  version={3.0.0},
+  version={4.0.0},
   publisher={Hugging Face},
   howpublished={\url{https://huggingface.co/datasets/BYU-Idaho/Web-Content}}
 }
@@ -344,4 +437,4 @@ Internal BYU-Idaho use. Contact: ai-team@byui.edu
 
 ---
 
-**Enterprise-Ready:** This dataset features advanced enrichment and filtering for production AI applications. With category classification, quality scoring, and reading levels, it's optimized for intelligent routing, quality filtering, and audience-appropriate responses.
+**State-of-the-Art:** This is the most feature-rich university web content dataset available, combining quality filtering, categorization, quality scoring, reading levels, AND comprehensive NLP enrichment with entity extraction, acronym detection, and domain terminology. Perfect for advanced RAG, semantic search, and intelligent educational AI applications.

data-00000-of-00001.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c71864a83f8feee2fe049847b136dd8bdee96bb3fd475d48a07893bb2ed23b44
-size 3036330
+oid sha256:ee7b1b8a2b79c8a620c2f7e9ca6757d86af6e8251d2f011ec6822f1a02262a0d
+size 3459836

dataset_info.json

@@ -1,7 +1,7 @@
 {
-  "dataset_name": "byui-web-content-enhanced",
-  "version": "3.0.0",
-  "description": "Ultra-high-quality BYU-Idaho web content with category classification and quality scores",
+  "dataset_name": "byui-web-content-nlp-enhanced",
+  "version": "4.0.0",
+  "description": "Ultra-high-quality BYU-Idaho web content with NLP enrichment: entities, acronyms, key phrases",
   "features": {
     "index": {
       "dtype": "int64",
@@ -42,6 +42,31 @@
     "reading_level": {
       "dtype": "float64",
       "_type": "Value"
+    },
+    "entities": {
+      "dtype": "string",
+      "_type": "Value",
+      "description": "JSON: {organizations, locations, programs, people}"
+    },
+    "byui_terms": {
+      "dtype": "string",
+      "_type": "Value",
+      "description": "JSON: List of BYU-Idaho specific terms"
+    },
+    "acronyms": {
+      "dtype": "string",
+      "_type": "Value",
+      "description": "JSON: {acronym: expansion}"
+    },
+    "key_phrases": {
+      "dtype": "string",
+      "_type": "Value",
+      "description": "JSON: List of important action phrases"
+    },
+    "domain_ngrams": {
+      "dtype": "string",
+      "_type": "Value",
+      "description": "JSON: List of common domain-specific phrases"
     }
   }
 }

state.json

@@ -4,6 +4,6 @@
       "filename": "data-00000-of-00001.parquet"
     }
   ],
-  "_fingerprint": "byui_web_content_enhanced_v3",
+  "_fingerprint": "byui_web_content_nlp_v4",
   "_format_type": "parquet"
 }