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+---
+language: mg
+language_name: Malagasy
+language_family: austronesian_malagasy
+tags:
+  - wikilangs
+  - nlp
+  - tokenizer
+  - embeddings
+  - n-gram
+  - markov
+  - wikipedia
+  - feature-extraction
+  - sentence-similarity
+  - tokenization
+  - n-grams
+  - markov-chain
+  - text-mining
+  - fasttext
+  - babelvec
+  - vocabulous
+  - vocabulary
+  - monolingual
+  - family-austronesian_malagasy
+license: mit
+library_name: wikilangs
+pipeline_tag: text-generation
+datasets:
+  - omarkamali/wikipedia-monthly
+dataset_info:
+  name: wikipedia-monthly
+  description: Monthly snapshots of Wikipedia articles across 300+ languages
+metrics:
+  - name: best_compression_ratio
+    type: compression
+    value: 4.455
+  - name: best_isotropy
+    type: isotropy
+    value: 0.8042
+  - name: vocabulary_size
+    type: vocab
+    value: 0
+generated: 2026-01-10
+---
+
+# Malagasy - Wikilangs Models
+## Comprehensive Research Report & Full Ablation Study
+
+This repository contains NLP models trained and evaluated by Wikilangs, specifically on **Malagasy** Wikipedia data.
+We analyze tokenizers, n-gram models, Markov chains, vocabulary statistics, and word embeddings.
+
+## 📋 Repository Contents
+
+### Models & Assets
+
+- Tokenizers (8k, 16k, 32k, 64k)
+- N-gram models (2, 3, 4, 5-gram)
+- Markov chains (context of 1, 2, 3, 4 and 5)
+- Subword N-gram and Markov chains
+- Embeddings in various sizes and dimensions (aligned and unaligned)
+- Language Vocabulary
+- Language Statistics
+
+![Performance Dashboard](visualizations/performance_dashboard.png)
+
+### Analysis and Evaluation
+
+- [1. Tokenizer Evaluation](#1-tokenizer-evaluation)
+- [2. N-gram Model Evaluation](#2-n-gram-model-evaluation)
+- [3. Markov Chain Evaluation](#3-markov-chain-evaluation)
+- [4. Vocabulary Analysis](#4-vocabulary-analysis)
+- [5. Word Embeddings Evaluation](#5-word-embeddings-evaluation)
+- [6. Morphological Analysis (Experimental)](#6--morphological-analysis-experimental)
+- [7. Summary & Recommendations](#7-summary--recommendations)
+- [Metrics Glossary](#appendix-metrics-glossary--interpretation-guide)
+- [Visualizations Index](#visualizations-index)
+
+---
+## 1. Tokenizer Evaluation
+
+![Tokenizer Compression](visualizations/tokenizer_compression.png)
+
+![Tokenizer Fertility](visualizations/tokenizer_fertility.png)
+
+![Tokenizer OOV](visualizations/tokenizer_oov.png)
+
+![Total Tokens](visualizations/tokenizer_total_tokens.png)
+
+### Results
+
+| Vocab Size | Compression | Avg Token Len | UNK Rate | Total Tokens |
+|------------|-------------|---------------|----------|--------------|
+| **8k** | 3.717x | 3.72 | 1.0106% | 763,492 |
+| **16k** | 4.029x | 4.03 | 1.0955% | 704,362 |
+| **32k** | 4.266x | 4.27 | 1.1597% | 665,323 |
+| **64k** | 4.455x 🏆 | 4.46 | 1.2113% | 637,017 |
+
+### Tokenization Examples
+
+Below are sample sentences tokenized with each vocabulary size:
+
+**Sample 1:** `I Taquaritinga dia kaominina ao , ao amin'i . Jeografia . Ny isam-ponina dia 56....`
+
+| Vocab | Tokens | Count |
+|-------|--------|-------|
+| 8k | `▁i ▁ta qu arit inga ▁dia ▁kaominina ▁ao ▁, ▁ao ... (+34 more)` | 44 |
+| 16k | `▁i ▁ta qu arit inga ▁dia ▁kaominina ▁ao ▁, ▁ao ... (+34 more)` | 44 |
+| 32k | `▁i ▁ta qu arit inga ▁dia ▁kaominina ▁ao ▁, ▁ao ... (+34 more)` | 44 |
+| 64k | `▁i ▁taqu aritinga ▁dia ▁kaominina ▁ao ▁, ▁ao ▁amin ' ... (+32 more)` | 42 |
+
+**Sample 2:** `Zoltán Stieber dia mpilalao baolina kitra teraka ny 16 Oktobra tao Hongaria Jere...`
+
+| Vocab | Tokens | Count |
+|-------|--------|-------|
+| 8k | `▁z ol t án ▁st i eb er ▁dia ▁mpilalao ... (+16 more)` | 26 |
+| 16k | `▁z olt án ▁st i eber ▁dia ▁mpilalao ▁baolina ▁kitra ... (+13 more)` | 23 |
+| 32k | `▁zoltán ▁st i eber ▁dia ▁mpilalao ▁baolina ▁kitra ▁teraka ▁ny ... (+11 more)` | 21 |
+| 64k | `▁zoltán ▁sti eber ▁dia ▁mpilalao ▁baolina ▁kitra ▁teraka ▁ny ▁ ... (+10 more)` | 20 |
+
+**Sample 3:** `Rutger Backe dia mpilalao baolina kitra mizaka ny zom-pirenen'i Soeda teraka ny ...`
+
+| Vocab | Tokens | Count |
+|-------|--------|-------|
+| 8k | `▁r ut ger ▁ba cke ▁dia ▁mpilalao ▁baolina ▁kitra ▁mizaka ... (+18 more)` | 28 |
+| 16k | `▁rut ger ▁ba cke ▁dia ▁mpilalao ▁baolina ▁kitra ▁mizaka ▁ny ... (+17 more)` | 27 |
+| 32k | `▁rut ger ▁ba cke ▁dia ▁mpilalao ▁baolina ▁kitra ▁mizaka ▁ny ... (+17 more)` | 27 |
+| 64k | `▁rut ger ▁ba cke ▁dia ▁mpilalao ▁baolina ▁kitra ▁mizaka ▁ny ... (+17 more)` | 27 |
+
+
+### Key Findings
+
+- **Best Compression:** 64k achieves 4.455x compression
+- **Lowest UNK Rate:** 8k with 1.0106% unknown tokens
+- **Trade-off:** Larger vocabularies improve compression but increase model size
+- **Recommendation:** 32k vocabulary provides optimal balance for production use
+
+---
+## 2. N-gram Model Evaluation
+
+![N-gram Perplexity](visualizations/ngram_perplexity.png)
+
+![N-gram Unique](visualizations/ngram_unique.png)
+
+![N-gram Coverage](visualizations/ngram_coverage.png)
+
+### Results
+
+| N-gram | Variant | Perplexity | Entropy | Unique N-grams | Top-100 Coverage | Top-1000 Coverage |
+|--------|---------|------------|---------|----------------|------------------|-------------------|
+| **2-gram** | Word | 3,283 | 11.68 | 138,920 | 38.8% | 67.4% |
+| **2-gram** | Subword | 188 🏆 | 7.55 | 7,308 | 76.8% | 99.3% |
+| **3-gram** | Word | 6,811 | 12.73 | 327,650 | 31.9% | 62.3% |
+| **3-gram** | Subword | 1,135 | 10.15 | 56,079 | 43.5% | 83.4% |
+| **4-gram** | Word | 13,815 | 13.75 | 695,396 | 27.5% | 57.0% |
+| **4-gram** | Subword | 4,270 | 12.06 | 297,339 | 28.3% | 63.5% |
+| **5-gram** | Word | 15,415 | 13.91 | 666,811 | 25.9% | 55.7% |
+| **5-gram** | Subword | 10,797 | 13.40 | 801,473 | 21.0% | 52.1% |
+
+### Top 5 N-grams by Size
+
+**2-grams (Word):**
+
+| Rank | N-gram | Count |
+|------|--------|-------|
+| 1 | `amin ny` | 363,322 |
+| 2 | `andro taona` | 205,790 |
+| 3 | `ao amin` | 204,188 |
+| 4 | `au au` | 199,079 |
+| 5 | `au andro` | 199,066 |
+
+**3-grams (Word):**
+
+| Rank | N-gram | Count |
+|------|--------|-------|
+| 1 | `au andro taona` | 199,066 |
+| 2 | `au au andro` | 199,066 |
+| 3 | `ao amin ny` | 165,787 |
+| 4 | `tamin ny taona` | 75,724 |
+| 5 | `taona au au` | 52,606 |
+
+**4-grams (Word):**
+
+| Rank | N-gram | Count |
+|------|--------|-------|
+| 1 | `au au andro taona` | 199,066 |
+| 2 | `au andro taona au` | 52,606 |
+| 3 | `andro taona au au` | 52,606 |
+| 4 | `taona au au andro` | 52,598 |
+| 5 | `amin ny faritr i` | 42,015 |
+
+**5-grams (Word):**
+
+| Rank | N-gram | Count |
+|------|--------|-------|
+| 1 | `au andro taona au au` | 52,606 |
+| 2 | `au au andro taona au` | 52,606 |
+| 3 | `andro taona au au andro` | 52,598 |
+| 4 | `taona au au andro taona` | 52,598 |
+| 5 | `ao amin ny faritr i` | 41,743 |
+
+**2-grams (Subword):**
+
+| Rank | N-gram | Count |
+|------|--------|-------|
+| 1 | `y _` | 2,972,630 |
+| 2 | `a _` | 2,871,965 |
+| 3 | `a n` | 2,624,146 |
+| 4 | `_ a` | 2,225,943 |
+| 5 | `n y` | 2,058,703 |
+
+**3-grams (Subword):**
+
+| Rank | N-gram | Count |
+|------|--------|-------|
+| 1 | `n y _` | 1,991,132 |
+| 2 | `n a _` | 984,036 |
+| 3 | `_ n y` | 972,813 |
+| 4 | `m i n` | 698,997 |
+| 5 | `a n a` | 687,522 |
+
+**4-grams (Subword):**
+
+| Rank | N-gram | Count |
+|------|--------|-------|
+| 1 | `_ n y _` | 971,989 |
+| 2 | `a m i n` | 574,682 |
+| 3 | `m i n '` | 543,499 |
+| 4 | `' n y _` | 517,014 |
+| 5 | `n ' n y` | 516,967 |
+
+**5-grams (Subword):**
+
+| Rank | N-gram | Count |
+|------|--------|-------|
+| 1 | `a m i n '` | 543,348 |
+| 2 | `n ' n y _` | 516,918 |
+| 3 | `_ d i a _` | 465,119 |
+| 4 | `_ a m i n` | 438,819 |
+| 5 | `a u ) _ a` | 398,149 |
+
+
+### Key Findings
+
+- **Best Perplexity:** 2-gram (subword) with 188
+- **Entropy Trend:** Decreases with larger n-grams (more predictable)
+- **Coverage:** Top-1000 patterns cover ~52% of corpus
+- **Recommendation:** 4-gram or 5-gram for best predictive performance
+
+---
+## 3. Markov Chain Evaluation
+
+![Markov Entropy](visualizations/markov_entropy.png)
+
+![Markov Contexts](visualizations/markov_contexts.png)
+
+![Markov Branching](visualizations/markov_branching.png)
+
+### Results
+
+| Context | Variant | Avg Entropy | Perplexity | Branching Factor | Unique Contexts | Predictability |
+|---------|---------|-------------|------------|------------------|-----------------|----------------|
+| **1** | Word | 0.6521 | 1.571 | 4.93 | 355,569 | 34.8% |
+| **1** | Subword | 0.6364 | 1.554 | 5.02 | 4,923 | 36.4% |
+| **2** | Word | 0.2834 | 1.217 | 1.88 | 1,748,434 | 71.7% |
+| **2** | Subword | 0.7914 | 1.731 | 4.56 | 24,686 | 20.9% |
+| **3** | Word | 0.1358 | 1.099 | 1.33 | 3,283,841 | 86.4% |
+| **3** | Subword | 0.8149 | 1.759 | 4.15 | 112,579 | 18.5% |
+| **4** | Word | 0.0673 🏆 | 1.048 | 1.15 | 4,348,637 | 93.3% |
+| **4** | Subword | 0.6559 | 1.576 | 3.01 | 467,417 | 34.4% |
+
+### Generated Text Samples (Word-based)
+
+Below are text samples generated from each word-based Markov chain model:
+
+**Context Size 1:**
+
+1. `ny masoandro mitatao ho an drenirano sy tsy hita eo amin ny fivavahana iraniana manodidina amin`
+2. `dia ary maty tamin ny toerana avo indrindra dia tanàna ao amin ny fehiben ny insee`
+3. `amin ny insee dia degre jereo koa hainkintana zavatra ara daharanjarahasin ilay kaominina ao amin ny`
+
+**Context Size 2:**
+
+1. `amin ny boribory lavoraryizay antsoina koa hoe excentricité amin ny soratra desimaly ny faritr i nou...`
+2. `andro taona au au andro taona karenfletch au au andro taona bomans rg au au andro taona`
+3. `ao amin ny 0 2 0 3 ary manana hafanana eo amin ny fivondronan i guéret ao`
+
+**Context Size 3:**
+
+1. `au andro taona jb13 au au andro taona ja59 au au andro taona xn45 au au andro taona`
+2. `au au andro taona tk27 au au andro taona qj2 au au andro taona au au andro taona`
+3. `ao amin ny vondronosy maley ho aty madagasikara notarihin i roger le goff no ben ny tanàna mandritry`
+
+**Context Size 4:**
+
+1. `au au andro taona oe4 au au andro taona sq3 au au andro taona au au andro taona om23`
+2. `au andro taona au au andro taona au au andro taona wp3 au au andro taona xy4 au au`
+3. `andro taona au au andro taona au au andro taona sg92 au au andro taona au au andro taona`
+
+
+### Generated Text Samples (Subword-based)
+
+Below are text samples generated from each subword-based Markov chain model:
+
+**Context Size 1:**
+
+1. `asogrewwrau)_any`
+2. `_aom4)_a_eliantr`
+3. `navony_bamiieser`
+
+**Context Size 2:**
+
+1. `y_mats.com-ponial`
+2. `a_dia_sy_hity_sy_`
+3. `andray_fy_ny_ambo`
+
+**Context Size 3:**
+
+1. `ny_ary_olomer_sns.`
+2. `na_rohy_i_juantsah`
+3. `_ny_ham-panodikoro`
+
+**Context Size 4:**
+
+1. `_ny_14_dia_mpilala_`
+2. `amin'_i_bernambaràn`
+3. `min'_ny_faritimes,_`
+
+
+### Key Findings
+
+- **Best Predictability:** Context-4 (word) with 93.3% predictability
+- **Branching Factor:** Decreases with context size (more deterministic)
+- **Memory Trade-off:** Larger contexts require more storage (467,417 contexts)
+- **Recommendation:** Context-3 or Context-4 for text generation
+
+---
+## 4. Vocabulary Analysis
+
+![Zipf's Law](visualizations/zipf_law.png)
+
+![Top Words](visualizations/top20_words.png)
+
+![Coverage Curve](visualizations/vocab_coverage.png)
+
+### Statistics
+
+| Metric | Value |
+|--------|-------|
+| Vocabulary Size | 186,416 |
+| Total Tokens | 12,311,117 |
+| Mean Frequency | 66.04 |
+| Median Frequency | 3 |
+| Frequency Std Dev | 4301.01 |
+
+### Most Common Words
+
+| Rank | Word | Frequency |
+|------|------|-----------|
+| 1 | ny | 1,518,386 |
+| 2 | dia | 465,913 |
+| 3 | amin | 435,633 |
+| 4 | au | 412,623 |
+| 5 | i | 399,465 |
+| 6 | taona | 314,686 |
+| 7 | ao | 283,721 |
+| 8 | andro | 214,534 |
+| 9 | ary | 149,725 |
+| 10 | tamin | 113,939 |
+
+### Least Common Words (from vocabulary)
+
+| Rank | Word | Frequency |
+|------|------|-----------|
+| 1 | clavaud | 2 |
+| 2 | holaboay | 2 |
+| 3 | olaboay | 2 |
+| 4 | marggie | 2 |
+| 5 | xiomara | 2 |
+| 6 | tapias | 2 |
+| 7 | firmo | 2 |
+| 8 | gentofte | 2 |
+| 9 | amalienborg | 2 |
+| 10 | vyborg | 2 |
+
+### Zipf's Law Analysis
+
+| Metric | Value |
+|--------|-------|
+| Zipf Coefficient | 1.2392 |
+| R² (Goodness of Fit) | 0.998231 |
+| Adherence Quality | **excellent** |
+
+### Coverage Analysis
+
+| Top N Words | Coverage |
+|-------------|----------|
+| Top 100 | 60.0% |
+| Top 1,000 | 81.4% |
+| Top 5,000 | 89.6% |
+| Top 10,000 | 92.3% |
+
+### Key Findings
+
+- **Zipf Compliance:** R²=0.9982 indicates excellent adherence to Zipf's law
+- **High Frequency Dominance:** Top 100 words cover 60.0% of corpus
+- **Long Tail:** 176,416 words needed for remaining 7.7% coverage
+
+---
+## 5. Word Embeddings Evaluation
+
+![Embedding Isotropy](visualizations/embedding_isotropy.png)
+
+![Similarity Matrix](visualizations/embedding_similarity.png)
+
+![t-SNE Words](visualizations/tsne_words.png)
+
+![t-SNE Sentences](visualizations/tsne_sentences.png)
+
+
+### 5.1 Cross-Lingual Alignment
+
+![Alignment Quality](visualizations/embedding_alignment_quality.png)
+
+![Multilingual t-SNE](visualizations/embedding_tsne_multilingual.png)
+
+
+### 5.2 Model Comparison
+
+| Model | Dimension | Isotropy | Semantic Density | Alignment R@1 | Alignment R@10 |
+|-------|-----------|----------|------------------|---------------|----------------|
+| **mono_32d** | 32 | 0.8042 | 0.3503 | N/A | N/A |
+| **mono_64d** | 64 | 0.7680 | 0.2980 | N/A | N/A |
+| **mono_128d** | 128 | 0.7205 | 0.2509 | N/A | N/A |
+| **aligned_32d** | 32 | 0.8042 🏆 | 0.3596 | 0.0820 | 0.3280 |
+| **aligned_64d** | 64 | 0.7680 | 0.2994 | 0.1540 | 0.4960 |
+| **aligned_128d** | 128 | 0.7205 | 0.2597 | 0.2000 | 0.5660 |
+
+### Key Findings
+
+- **Best Isotropy:** aligned_32d with 0.8042 (more uniform distribution)
+- **Semantic Density:** Average pairwise similarity of 0.3030. Lower values indicate better semantic separation.
+- **Alignment Quality:** Aligned models achieve up to 20.0% R@1 in cross-lingual retrieval.
+- **Recommendation:** 128d aligned for best cross-lingual performance
+
+---
+## 6.  Morphological Analysis (Experimental)
+
+This section presents an automated morphological analysis derived from the statistical divergence between word-level and subword-level models. By analyzing where subword predictability spikes and where word-level coverage fails, we can infer linguistic structures without supervised data.
+
+### 6.1 Productivity & Complexity
+
+| Metric | Value | Interpretation | Recommendation |
+|--------|-------|----------------|----------------|
+| Productivity Index | **5.000** | High morphological productivity | Reliable analysis |
+| Idiomaticity Gap | **0.070** | Low formulaic content | - |
+
+### 6.2 Affix Inventory (Productive Units)
+
+These are the most productive prefixes and suffixes identified by sampling the vocabulary for global substitutability patterns. A unit is considered an affix if stripping it leaves a valid stem that appears in other contexts.
+
+#### Productive Prefixes
+| Prefix | Examples |
+|--------|----------|
+| `-s` | stenopetalum, stenay, sumiyoshi |
+| `-a` | andriamarobasy, anggun, aboville |
+| `-r` | reignat, rm97, raty |
+| `-t` | tm67, td34, tp34 |
+| `-c` | christensen, ce6, celentano |
+| `-b` | bakkoury, bev, bakr |
+| `-f` | famantaranavaratra, frisano, fanandraman |
+| `-g` | gp6, gq54, gc61 |
+
+#### Productive Suffixes
+| Suffix | Examples |
+|--------|----------|
+| `-a` | donnera, kwaśniewska, famantaranavaratra |
+| `-na` | fanasokajiana, andaminana, hampijoroana |
+| `-n` | nosoniavin, anggun, christensen |
+| `-s` | pégairolles, aups, tauxières |
+| `-e` | aboville, bartole, louze |
+| `-y` | andriamarobasy, namitany, stenay |
+| `-o` | frisano, celentano, shapiro |
+| `-i` | oerstedii, sumiyoshi, salviani |
+
+### 6.3 Bound Stems (Lexical Roots)
+
+Bound stems are high-frequency subword units that are semantically cohesive but rarely appear as standalone words. These often correspond to the 'core' of a word that requires inflection or derivation to be valid.
+
+| Stem | Cohesion | Substitutability | Examples |
+|------|----------|------------------|----------|
+| `inin` | 2.33x | 55 contexts | minin, vining, jining |
+| `indr` | 1.81x | 124 contexts | indre, indri, indry |
+| `andr` | 1.49x | 336 contexts | andry, andro, andra |
+| `ndra` | 1.67x | 176 contexts | ondra, andra, indra |
+| `itra` | 1.69x | 141 contexts | mitra, ritra, kitra |
+| `iana` | 1.64x | 164 contexts | kiana, riana, niana |
+| `ndri` | 1.63x | 161 contexts | endri, indri, andri |
+| `ants` | 1.70x | 116 contexts | sants, antsa, wants |
+| `ahar` | 1.66x | 111 contexts | nahar, bahar, ahary |
+| `ndro` | 1.58x | 111 contexts | andro, indro, androy |
+| `inta` | 1.74x | 60 contexts | vinta, linta, kinta |
+| `ntan` | 1.49x | 111 contexts | entan, entana, antany |
+
+### 6.4 Affix Compatibility (Co-occurrence)
+
+This table shows which prefixes and suffixes most frequently co-occur on the same stems, revealing the 'stacking' rules of the language's morphology.
+
+| Prefix | Suffix | Frequency | Examples |
+|--------|--------|-----------|----------|
+| `-a` | `-a` | 134 words | ansikilika, aminata |
+| `-f` | `-a` | 128 words | fanononana, fanaparitahana |
+| `-f` | `-na` | 105 words | fanononana, fanaparitahana |
+| `-h` | `-a` | 103 words | hetaheta, hamitika |
+| `-t` | `-a` | 77 words | theodosia, tuberifera |
+| `-s` | `-a` | 64 words | serrania, sirasida |
+| `-f` | `-n` | 62 words | furlan, flaxman |
+| `-c` | `-s` | 61 words | citées, cisterciensis |
+| `-a` | `-na` | 56 words | alamàna, andriankotonavalona |
+| `-b` | `-a` | 52 words | bizantioma, botovasoa |
+
+### 6.5 Recursive Morpheme Segmentation
+
+Using **Recursive Hierarchical Substitutability**, we decompose complex words into their constituent morphemes. This approach handles nested affixes (e.g., `prefix-prefix-root-suffix`).
+
+| Word | Suggested Split | Confidence | Stem |
+|------|-----------------|------------|------|
+| miratoerana | **`mi-ra-toerana`** | 7.5 | `toerana` |
+| namoronany | **`namoro-na-ny`** | 7.5 | `na` |
+| fanakanana | **`fanaka-na-na`** | 7.5 | `na` |
+| newfoundland | **`newfoundl-an-d`** | 7.5 | `an` |
+| fampitany | **`fampit-a-ny`** | 7.5 | `a` |
+| firenenena | **`firenen-e-na`** | 7.5 | `e` |
+| holazainao | **`holazai-na-o`** | 7.5 | `na` |
+| boetticher | **`boetti-ch-er`** | 7.5 | `ch` |
+| cucurbiteae | **`cucurbite-a-e`** | 7.5 | `a` |
+| cobergher | **`coberg-h-er`** | 7.5 | `h` |
+| fankanesana | **`fankanes-a-na`** | 7.5 | `a` |
+| fahatoranana | **`fahatora-na-na`** | 7.5 | `na` |
+| nanohanany | **`nanoha-na-ny`** | 7.5 | `na` |
+| anamafana | **`anamaf-a-na`** | 7.5 | `a` |
+| fampirantiana | **`fampiranti-a-na`** | 7.5 | `a` |
+
+### 6.6 Linguistic Interpretation
+
+> **Automated Insight:**
+The language Malagasy shows high morphological productivity. The subword models are significantly more efficient than word models, suggesting a rich system of affixation or compounding.
+
+---
+## 7. Summary & Recommendations
+
+![Performance Dashboard](visualizations/performance_dashboard.png)
+
+### Production Recommendations
+
+| Component | Recommended | Rationale |
+|-----------|-------------|-----------|
+| Tokenizer | **64k BPE** | Best compression (4.46x) |
+| N-gram | **2-gram** | Lowest perplexity (188) |
+| Markov | **Context-4** | Highest predictability (93.3%) |
+| Embeddings | **100d** | Balanced semantic capture and isotropy |
+
+
+---
+## Appendix: Metrics Glossary & Interpretation Guide
+
+This section provides definitions, intuitions, and guidance for interpreting the metrics used throughout this report.
+
+### Tokenizer Metrics
+
+**Compression Ratio**
+> *Definition:* The ratio of characters to tokens (chars/token). Measures how efficiently the tokenizer represents text.
+>
+> *Intuition:* Higher compression means fewer tokens needed to represent the same text, reducing sequence lengths for downstream models. A 3x compression means ~3 characters per token on average.
+>
+> *What to seek:* Higher is generally better for efficiency, but extremely high compression may indicate overly aggressive merging that loses morphological information.
+
+**Average Token Length (Fertility)**
+> *Definition:* Mean number of characters per token produced by the tokenizer.
+>
+> *Intuition:* Reflects the granularity of tokenization. Longer tokens capture more context but may struggle with rare words; shorter tokens are more flexible but increase sequence length.
+>
+> *What to seek:* Balance between 2-5 characters for most languages. Arabic/morphologically-rich languages may benefit from slightly longer tokens.
+
+**Unknown Token Rate (OOV Rate)**
+> *Definition:* Percentage of tokens that map to the unknown/UNK token, indicating words the tokenizer cannot represent.
+>
+> *Intuition:* Lower OOV means better vocabulary coverage. High OOV indicates the tokenizer encounters many unseen character sequences.
+>
+> *What to seek:* Below 1% is excellent; below 5% is acceptable. BPE tokenizers typically achieve very low OOV due to subword fallback.
+
+### N-gram Model Metrics
+
+**Perplexity**
+> *Definition:* Measures how "surprised" the model is by test data. Mathematically: 2^(cross-entropy). Lower values indicate better prediction.
+>
+> *Intuition:* If perplexity is 100, the model is as uncertain as if choosing uniformly among 100 options at each step. A perplexity of 10 means effectively choosing among 10 equally likely options.
+>
+> *What to seek:* Lower is better. Perplexity decreases with larger n-grams (more context). Values vary widely by language and corpus size.
+
+**Entropy**
+> *Definition:* Average information content (in bits) needed to encode the next token given the context. Related to perplexity: perplexity = 2^entropy.
+>
+> *Intuition:* High entropy means high uncertainty/randomness; low entropy means predictable patterns. Natural language typically has entropy between 1-4 bits per character.
+>
+> *What to seek:* Lower entropy indicates more predictable text patterns. Entropy should decrease as n-gram size increases.
+
+**Coverage (Top-K)**
+> *Definition:* Percentage of corpus occurrences explained by the top K most frequent n-grams.
+>
+> *Intuition:* High coverage with few patterns indicates repetitive/formulaic text; low coverage suggests diverse vocabulary usage.
+>
+> *What to seek:* Depends on use case. For language modeling, moderate coverage (40-60% with top-1000) is typical for natural text.
+
+### Markov Chain Metrics
+
+**Average Entropy**
+> *Definition:* Mean entropy across all contexts, measuring average uncertainty in next-word prediction.
+>
+> *Intuition:* Lower entropy means the model is more confident about what comes next. Context-1 has high entropy (many possible next words); Context-4 has low entropy (few likely continuations).
+>
+> *What to seek:* Decreasing entropy with larger context sizes. Very low entropy (<0.1) indicates highly deterministic transitions.
+
+**Branching Factor**
+> *Definition:* Average number of unique next tokens observed for each context.
+>
+> *Intuition:* High branching = many possible continuations (flexible but uncertain); low branching = few options (predictable but potentially repetitive).
+>
+> *What to seek:* Branching factor should decrease with context size. Values near 1.0 indicate nearly deterministic chains.
+
+**Predictability**
+> *Definition:* Derived metric: (1 - normalized_entropy) × 100%. Indicates how deterministic the model's predictions are.
+>
+> *Intuition:* 100% predictability means the next word is always certain; 0% means completely random. Real text falls between these extremes.
+>
+> *What to seek:* Higher predictability for text generation quality, but too high (>98%) may produce repetitive output.
+
+### Vocabulary & Zipf's Law Metrics
+
+**Zipf's Coefficient**
+> *Definition:* The slope of the log-log plot of word frequency vs. rank. Zipf's law predicts this should be approximately -1.
+>
+> *Intuition:* A coefficient near -1 indicates the corpus follows natural language patterns where a few words are very common and most words are rare.
+>
+> *What to seek:* Values between -0.8 and -1.2 indicate healthy natural language distribution. Deviations may suggest domain-specific or artificial text.
+
+**R² (Coefficient of Determination)**
+> *Definition:* Measures how well the linear fit explains the frequency-rank relationship. Ranges from 0 to 1.
+>
+> *Intuition:* R² near 1.0 means the data closely follows Zipf's law; lower values indicate deviation from expected word frequency patterns.
+>
+> *What to seek:* R² > 0.95 is excellent; > 0.99 indicates near-perfect Zipf adherence typical of large natural corpora.
+
+**Vocabulary Coverage**
+> *Definition:* Cumulative percentage of corpus tokens accounted for by the top N words.
+>
+> *Intuition:* Shows how concentrated word usage is. If top-100 words cover 50% of text, the corpus relies heavily on common words.
+>
+> *What to seek:* Top-100 covering 30-50% is typical. Higher coverage indicates more repetitive text; lower suggests richer vocabulary.
+
+### Word Embedding Metrics
+
+**Isotropy**
+> *Definition:* Measures how uniformly distributed vectors are in the embedding space. Computed as the ratio of minimum to maximum singular values.
+>
+> *Intuition:* High isotropy (near 1.0) means vectors spread evenly in all directions; low isotropy means vectors cluster in certain directions, reducing expressiveness.
+>
+> *What to seek:* Higher isotropy generally indicates better-quality embeddings. Values > 0.1 are reasonable; > 0.3 is good. Lower-dimensional embeddings tend to have higher isotropy.
+
+**Average Norm**
+> *Definition:* Mean magnitude (L2 norm) of word vectors in the embedding space.
+>
+> *Intuition:* Indicates the typical "length" of vectors. Consistent norms suggest stable training; high variance may indicate some words are undertrained.
+>
+> *What to seek:* Relatively consistent norms across models. The absolute value matters less than consistency (low std deviation).
+
+**Cosine Similarity**
+> *Definition:* Measures angular similarity between vectors, ranging from -1 (opposite) to 1 (identical direction).
+>
+> *Intuition:* Words with similar meanings should have high cosine similarity. This is the standard metric for semantic relatedness in embeddings.
+>
+> *What to seek:* Semantically related words should score > 0.5; unrelated words should be near 0. Synonyms often score > 0.7.
+
+**t-SNE Visualization**
+> *Definition:* t-Distributed Stochastic Neighbor Embedding - a dimensionality reduction technique that preserves local structure for visualization.
+>
+> *Intuition:* Clusters in t-SNE plots indicate groups of semantically related words. Spread indicates vocabulary diversity; tight clusters suggest semantic coherence.
+>
+> *What to seek:* Meaningful clusters (e.g., numbers together, verbs together). Avoid over-interpreting distances - t-SNE preserves local, not global, structure.
+
+### General Interpretation Guidelines
+
+1. **Compare within model families:** Metrics are most meaningful when comparing models of the same type (e.g., 8k vs 64k tokenizer).
+2. **Consider trade-offs:** Better performance on one metric often comes at the cost of another (e.g., compression vs. OOV rate).
+3. **Context matters:** Optimal values depend on downstream tasks. Text generation may prioritize different metrics than classification.
+4. **Corpus influence:** All metrics are influenced by corpus characteristics. Wikipedia text differs from social media or literature.
+5. **Language-specific patterns:** Morphologically rich languages (like Arabic) may show different optimal ranges than analytic languages.
+
+
+### Visualizations Index
+
+| Visualization | Description |
+|---------------|-------------|
+| Tokenizer Compression | Compression ratios by vocabulary size |
+| Tokenizer Fertility | Average token length by vocabulary |
+| Tokenizer OOV | Unknown token rates |
+| Tokenizer Total Tokens | Total tokens by vocabulary |
+| N-gram Perplexity | Perplexity by n-gram size |
+| N-gram Entropy | Entropy by n-gram size |
+| N-gram Coverage | Top pattern coverage |
+| N-gram Unique | Unique n-gram counts |
+| Markov Entropy | Entropy by context size |
+| Markov Branching | Branching factor by context |
+| Markov Contexts | Unique context counts |
+| Zipf's Law | Frequency-rank distribution with fit |
+| Vocab Frequency | Word frequency distribution |
+| Top 20 Words | Most frequent words |
+| Vocab Coverage | Cumulative coverage curve |
+| Embedding Isotropy | Vector space uniformity |
+| Embedding Norms | Vector magnitude distribution |
+| Embedding Similarity | Word similarity heatmap |
+| Nearest Neighbors | Similar words for key terms |
+| t-SNE Words | 2D word embedding visualization |
+| t-SNE Sentences | 2D sentence embedding visualization |
+| Position Encoding | Encoding method comparison |
+| Model Sizes | Storage requirements |
+| Performance Dashboard | Comprehensive performance overview |
+
+---
+## About This Project
+
+### Data Source
+
+Models trained on [wikipedia-monthly](https://huggingface.co/datasets/omarkamali/wikipedia-monthly) - a monthly snapshot of Wikipedia articles across 300+ languages.
+
+### Project
+
+A project by **[Wikilangs](https://wikilangs.org)** - Open-source NLP models for every Wikipedia language.
+
+### Maintainer
+
+[Omar Kamali](https://omarkamali.com) - [Omneity Labs](https://omneitylabs.com)
+
+### Citation
+
+If you use these models in your research, please cite:
+
+```bibtex
+@misc{wikilangs2025,
+  author = {Kamali, Omar},
+  title = {Wikilangs: Open NLP Models for Wikipedia Languages},
+  year = {2025},
+  doi = {10.5281/zenodo.18073153},
+  publisher = {Zenodo},
+  url = {https://huggingface.co/wikilangs}
+  institution = {Omneity Labs}
+}
+```
+
+### License
+
+MIT License - Free for academic and commercial use.
+
+### Links
+
+- 🌐 Website: [wikilangs.org](https://wikilangs.org)
+- 🤗 Models: [huggingface.co/wikilangs](https://huggingface.co/wikilangs)
+- 📊 Data: [wikipedia-monthly](https://huggingface.co/datasets/omarkamali/wikipedia-monthly)
+- 👤 Author: [Omar Kamali](https://huggingface.co/omarkamali)
+- 🤝 Sponsor: [Featherless AI](https://featherless.ai)
+---
+*Generated by Wikilangs Models Pipeline*
+
+*Report Date: 2026-01-10 12:09:55*
diff --git a/mg_morph_tokenizer.json b/mg_morph_tokenizer.json
new file mode 100644
index 0000000000000000000000000000000000000000..a85a74a8851fb262ed174e61aed23b45bc108aca
--- /dev/null
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diff --git a/models/tokenizer/mg_tokenizer_16k.vocab b/models/tokenizer/mg_tokenizer_16k.vocab
new file mode 100644
index 0000000000000000000000000000000000000000..2bf999926221c1ed999b0a4fa4eef47ae6107d33
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+▁mameloka	-26795
+▁mireille	-26796
+▁misakana	-26797
+▁moramora	-26798
+▁morarano	-26799
+▁mpandalo	-26800
+▁mpihinan	-26801
+▁mpisoron	-26802
+▁mônazita	-26803
+▁nanamora	-26804
+▁nandroba	-26805
+▁nangonin	-26806
+▁nanteuil	-26807
+▁neandert	-26808
+▁nianjera	-26809
+▁nihazona	-26810
+▁nolazain	-26811
+▁paulette	-26812
+▁peshitta	-26813
+▁pinochet	-26814
+▁rosières	-26815
+▁sarangan	-26816
+▁saussure	-26817
+▁schröder	-26818
+▁selected	-26819
+▁sinagôga	-26820
+▁sjöstedt	-26821
+▁stanford	-26822
+▁tanalahy	-26823
+▁tantanan	-26824
+▁traktera	-26825
+▁tsindrin	-26826
+▁ulmaceae	-26827
+▁visigôty	-26828
+▁vokovoko	-26829
+▁volasira	-26830
+▁waldemar	-26831
+▁zabolôna	-26832
+▁zambézia	-26833
+analamanga	-26834
+mpanoratra	-26835
+oldenbourg	-26836
+pifohazana	-26837
+ôrtôdôksia	-26838
+▁acquaviva	-26839
+▁adansonia	-26840
+▁agapornis	-26841
+▁amboanala	-26842
+▁antoandro	-26843
+▁artemisia	-26844
+▁atlántico	-26845
+▁baldassar	-26846
+▁balthazar	-26847
+▁barnabasy	-26848
+▁bartolomé	-26849
+▁bernieria	-26850
+▁biodivers	-26851
+▁boliviana	-26852
+▁camembert	-26853
+▁cantabria	-26854
+▁champigny	-26855
+▁cornelisz	-26856
+▁cézallier	-26857
+▁dieulefit	-26858
+▁dipsaceus	-26859
+▁esperança	-26860
+▁establish	-26861
+▁fairfield	-26862
+▁fanakonam	-26863
+▁fanjifana	-26864
+▁ferrières	-26865
+▁fiarahana	-26866
+▁fifankaha	-26867
+▁filaminam	-26868
+▁fivarotan	-26869
+▁fôrmôzana	-26870
+▁haifiteny	-26871
+▁haikoriam	-26872
+▁hasideana	-26873
+▁hôlôferna	-26874
+▁inôkentio	-26875
+▁johansson	-26876
+▁joinville	-26877
+▁kominista	-26878
+▁latifolia	-26879
+▁lignières	-26880
+▁lombardia	-26881
+▁manjavona	-26882
+▁milatsaka	-26883
+▁mitsidika	-26884
+▁mussolini	-26885
+▁nabokôdôn	-26886
+▁nahatsapa	-26887
+▁nankalaza	-26888
+▁natahotra	-26889
+▁newcastle	-26890
+▁nianarany	-26891
+▁niorenany	-26892
+▁nogentais	-26893
+▁nohajaina	-26894
+▁nolazaina	-26895
+▁oleksandr	-26896
+▁sakamalao	-26897
+▁soatanàna	-26898
+▁stephanie	-26899
+▁stôikiana	-26900
+▁supérieur	-26901
+▁tanimatin	-26902
+▁tôkariana	-26903
+▁valcezard	-26904
+▁varavaran	-26905
+▁voakasika	-26906
+▁wuppertal	-26907
+▁zanatanin	-26908
+pifidianana	-26909
+▁ambohimana	-26910
+▁ambondrona	-26911
+▁andriamani	-26912
+▁ankohonany	-26913
+▁atsinanany	-26914
+▁australian	-26915
+▁autonomous	-26916
+▁beauregard	-26917
+▁bridgeport	-26918
+▁champenois	-26919
+▁compostela	-26920
+▁cordillera	-26921
+▁episkôpaly	-26922
+▁fahampiana	-26923
+▁fandiovana	-26924
+▁fiangonany	-26925
+▁fifankatia	-26926
+▁greenville	-26927
+▁guanajuato	-26928
+▁hanampiana	-26929
+▁hieronymus	-26930
+▁historique	-26931
+▁hitondrana	-26932
+▁hutchinson	-26933
+▁iogoslavia	-26934
+▁management	-26935
+▁manantitra	-26936
+▁mangotraka	-26937
+▁maroserana	-26938
+▁menarandra	-26939
+▁mizarazara	-26940
+▁monisipaly	-26941
+▁mouthoumet	-26942
+▁natsangany	-26943
+▁nikôdemôsy	-26944
+▁nipetrahan	-26945
+▁nitandrina	-26946
+▁nogadraina	-26947
+▁noheveriny	-26948
+▁notokanana	-26949
+▁orogoaiana	-26950
+▁patriarika	-26951
+▁patrocínio	-26952
+▁preterisma	-26953
+▁providence	-26954
+▁rakotondra	-26955
+▁sisintanin	-26956
+▁sundamomum	-26957
+▁sôsialisma	-26958
+▁voninahitr	-26959
+morontsiraka	-26960
+pandrenesana	-26961
+tarehimarika	-26962
+▁aleksandrov	-26963
+▁ambodimanga	-26964
+▁ampahefatry	-26965
+▁antrôpôlôga	-26966
+▁chamberlain	-26967
+▁conselheiro	-26968
+▁disprôsiôma	-26969
+▁fahambonian	-26970
+▁fampianaram	-26971
+▁fampihenana	-26972
+▁fampimirana	-26973
+▁faravohitra	-26974
+▁fihetsehana	-26975
+▁fiombonambe	-26976
+▁fivoriamben	-26977
+▁gadôliniôma	-26978
+▁jeôpôlitika	-26979
+▁milenarisma	-26980
+▁mullerornis	-26981
+▁nanandratra	-26982
+▁natoralisma	-26983
+▁nympheaceae	-26984
+▁pentecostal	-26985
+▁protopterus	-26986
+▁tsinjoarivo	-26987
+▁villamblard	-26988
+▁zanabintana	-26989
+pitondrantena	-26990
+▁andriantsoly	-26991
+▁antenantenan	-26992
+▁antsahadinta	-26993
+▁braunschweig	-26994
+▁broadcasting	-26995
+▁construction	-26996
+▁fahatanorany	-26997
+▁fitandremana	-26998
+▁linguistique	-26999
+▁manarakaraka	-27000
+▁manelanelana	-27001
+▁rakotomalala	-27002
+▁revôlisiônan	-27003
+▁streptopelia	-27004
+▁afindrafindra	-27005
+▁alexandrovich	-27006
+▁aostralianina	-27007
+▁epistemôlôjia	-27008
+▁fahasambarana	-27009
+▁fanapoizinana	-27010
+▁kônfosianisma	-27011
+▁kôngregasiôna	-27012
+▁mathématiques	-27013
+▁mpanoradalàna	-27014
+▁neufchâtelois	-27015
+▁sambiranensis	-27016
+▁fampandehanana	-27017
+▁fanatontoloana	-27018
+▁fieritreretana	-27019
+▁mihetsiketsika	-27020
+▁mpampihorohoro	-27021
+▁mpiandraikitra	-27022
+▁cryptosylvicola	-27023
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+▁->	-27084
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+▁jat	-27211
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+▁mop	-27218
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+▁saa	-27228
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+marin	-27289
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+oavam	-27297
+ohiny	-27298
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+omyia	-27302
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+order	-27304
+ossau	-27305
+othée	-27306
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+paham	-27308
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+peaux	-27310
+pfalz	-27311
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+pinia	-27313
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+sarts	-27320
+sizun	-27321
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+veyle	-27332
+viane	-27333
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+wayri	-27336
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+▁bôbô	-27355
+▁caus	-27356
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+▁cera	-27358
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+▁diôk	-27366
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+▁educ	-27369
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+▁foun	-27378
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+▁glou	-27380
+▁gout	-27381
+▁guaj	-27382
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+▁haky	-27384
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+▁kipr	-27396
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+▁kour	-27399
+▁kova	-27400
+▁ktes	-27401
+▁kuch	-27402
+▁labr	-27403
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+▁last	-27406
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+▁leth	-27408
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+▁madi	-27410
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+▁dušan	-27557
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+▁elmer	-27559
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+▁rémuzat	-27895
+▁sakaiza	-27896
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+▁suffolk	-27902
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+▁tongotr	-27907
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+▁lagrasse	-27990
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+▁magazine	-27993
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+▁mamadika	-27996
+▁mamarana	-27997
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+▁matoatoa	-28000
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+▁môrdekay	-28004
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+▁nanafaka	-28007
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+▁richland	-28020
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+▁tafavoaka	-28089
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+▁tenebrosa	-28092
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+▁vingeanne	-28097
+▁zosterops	-28098
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+panabeazana	-28100
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+▁adamantina	-28103
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+▁ampandrana	-28105
+▁anatrehany	-28106
+▁andalinana	-28107
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+▁bartholome	-28109
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+▁elefantina	-28115
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+▁fahadiovan	-28117
+▁fahalavoan	-28118
+▁faharesena	-28119
+▁fametrahan	-28120
+▁fandrobana	-28121
+▁fenomanana	-28122
+▁fiambenana	-28123
+▁fianianana	-28124
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+▁hampiditra	-28126
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+▁sagartiana	-28141
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+▁cinereiceps	-28157
+▁fahalianana	-28158
+▁fahasalamam	-28159
+▁fifanaraham	-28160
+▁fitandroana	-28161
+▁fividianana	-28162
+▁grandiflora	-28163
+▁habyarimana	-28164
+▁hampihenana	-28165
+▁hitsivolana	-28166
+▁kanibalisma	-28167
+▁kiniaroanda	-28168
+▁mampandroso	-28169
+▁marcantonio	-28170
+▁nampindrana	-28171
+▁nanambaràna	-28172
+▁nandrombaka	-28173
+▁narbonnaise	-28174
+▁nasandratra	-28175
+▁panicoideae	-28176
+▁prefektiora	-28177
+▁radiôaktifa	-28178
+▁tompontsika	-28179
+▁tsileondoza	-28180
+▁vatolatsaka	-28181
+▁vocabulaire	-28182
+▁akoamarinina	-28183
+▁andrianarivo	-28184
+▁benghalensis	-28185
+▁bibliothèque	-28186
+▁chesterfield	-28187
+▁civilisation	-28188
+▁fanapariaham	-28189
+▁fifandanjana	-28190
+▁fikirakirana	-28191
+▁firoboroboan	-28192
+▁fitsanganany	-28193
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+▁lohalaharana	-28195
+▁mihazakazaka	-28196
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+▁nasiônalisma	-28198
+▁rakotonirina	-28199
+▁salavantanin	-28200
+▁zanadralambo	-28201
+▁compositaceae	-28202
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+▁nampiroborobo	-28204
+▁nestôrianisma	-28205
+▁neôplatônisma	-28206
+▁superciliaris	-28207
+▁tompomenakely	-28208
+▁vakinisisaony	-28209
+▁zanakandriana	-28210
+montsaugeonnais	-28211
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+▁fahatanterahan	-28213
+▁manoritsoritra	-28214
+▁nabokôdônôzôra	-28215
+▁passifloraceae	-28216
+▁tsiambaratelon	-28217
+▁elektrômanetika	-28218
+▁faravodilanitra	-28219
+▁rajaonarimanana	-28220
+▁voasarimakirana	-28221
+',	-28222
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+iku	-28256
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+▁sansevieria	-31108
+▁sinkretisma	-31109
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+▁mikrôneziana	-31130
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+▁fahatongavany	-31147
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+▁namahanambasy	-31153
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+▁siphonochilus	-31157
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+▁chloropetoides	-31161
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+▁voalohandohany	-31163
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+'.	-31170
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+▁atsimoandrefan	-18385
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+▁famot	-18606
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+▁hydro	-18610
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+▁cuiabá	-18659
+▁dudley	-18660
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+▁jônasa	-18666
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+▁macapá	-18668
+▁manaus	-18669
+▁mivady	-18670
+▁nadaba	-18671
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+▁silvio	-18674
+▁tongan	-18675
+▁vahana	-18676
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+▁voasar	-18679
+▁víctor	-18680
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+▁alitara	-18689
+▁atokana	-18690
+▁chapman	-18691
+▁danièle	-18692
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+▁hamburg	-18700
+▁hampton	-18701
+▁hanaela	-18702
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+▁kikôngô	-18706
+▁kingdom	-18707
+▁lafatra	-18708
+▁lempona	-18709
+▁maliana	-18710
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+▁dakahlia	-18739
+▁fefiloha	-18740
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+▁niorenan	-18751
+▁pasadena	-18752
+▁pasitera	-18753
+▁reinhold	-18754
+▁rutaceae	-18755
+▁silikata	-18756
+▁tanindra	-18757
+▁verkiela	-18758
+▁votoatin	-18759
+▁zôdiakan	-18760
+pikarohana	-18761
+tsiarovana	-18762
+▁alexandra	-18763
+▁amsterdam	-18764
+▁ankiliabo	-18765
+▁atmôsfera	-18766
+▁avaratran	-18767
+▁catantops	-18768
+▁dommartin	-18769
+▁estoniana	-18770
+▁faradofay	-18771
+▁fiovaovan	-18772
+▁františek	-18773
+▁hamaliela	-18774
+▁havaozina	-18775
+▁meksikana	-18776
+▁metôdista	-18777
+▁misionera	-18778
+▁mohrungen	-18779
+▁mpamosavy	-18780
+▁mônastera	-18781
+▁nabateana	-18782
+▁namboarin	-18783
+▁nanatrika	-18784
+▁nazareana	-18785
+▁nivelatra	-18786
+▁notohanan	-18787
+▁novokarin	-18788
+▁noyonnais	-18789
+▁pakistana	-18790
+▁poméranie	-18791
+▁raharahan	-18792
+▁rehôbôama	-18793
+▁saintonge	-18794
+▁tanisaina	-18795
+▁tantsambo	-18796
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+ifangaroana	-18798
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+▁aleksandro	-18801
+▁andohahela	-18802
+▁ankilizato	-18803
+▁belleville	-18804
+▁eichhornia	-18805
+▁fanakonana	-18806
+▁fanambaràn	-18807
+▁fanendrena	-18808
+▁fanofanana	-18809
+▁hahalanian	-18810
+▁hamerenana	-18811
+▁hisorohana	-18812
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+▁manondraka	-18814
+▁maximilien	-18815
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+▁miaramilan	-18817
+▁mônôteista	-18818
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+▁sapotaceae	-18821
+▁strelitzia	-18822
+▁sôsiôlôjia	-18823
+▁tsimanompo	-18824
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+▁ampianarina	-18826
+▁fandehanana	-18827
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+▁miaramilany	-18829
+▁mizakatenan	-18830
+▁notsidihina	-18831
+▁tambajotran	-18832
+▁akorandriaka	-18833
+▁cyanthillium	-18834
+▁fifamatorana	-18835
+▁hanamafisana	-18836
+▁isankarazany	-18837
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+▁vocabula	-25678
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+▁antongila	-25685
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+▁damaskosy	-25692
+▁doulevant	-25693
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+▁eorôpiôma	-25697
+▁eritreana	-25698
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+▁fahadimin	-25700
+▁fahamendr	-25701
+▁fahavitan	-25702
+▁farifitra	-25703
+▁fievenana	-25704
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+▁fintinina	-25706
+▁fisaonana	-25707
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+▁gallimard	-25709
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+▁gütersloh	-25713
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+▁mifikitra	-25728
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+▁thüringen	-25747
+▁tongobory	-25748
+▁trémoille	-25749
+▁tsipelina	-25750
+▁volodymyr	-25751
+▁volombava	-25752
+▁vonizongo	-25753
+boajanahary	-25754
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+ifanarahana	-25756
+lavorariana	-25757
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+▁ahasoerôsy	-25763
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+▁fanapoizin	-25771
+▁fandreseny	-25772
+▁fibebahana	-25773
+▁fitetezana	-25774
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+▁harafesina	-25777
+▁hiantsoana	-25778
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+▁kilahimena	-25780
+▁kôsmôlôjia	-25781
+▁manameloka	-25782
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+▁marovatana	-25784
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+▁miharihary	-25786
+▁milazalaza	-25787
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+▁môldaviana	-25791
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+▁nascimento	-25793
+▁nifanaraka	-25794
+▁nisambotra	-25795
+▁niterahany	-25796
+▁nonthaburi	-25797
+▁novokarina	-25798
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+▁prômetiôma	-25800
+▁respublika	-25801
+▁roifantaka	-25802
+▁sahozanina	-25803
+▁sokaidîtra	-25804
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+▁abderrahman	-25806
+▁ampahafolon	-25807
+▁belarosiana	-25808
+▁chaumontais	-25809
+▁clermontais	-25810
+▁cyclanthera	-25811
+▁fahatantera	-25812
+▁fahateraham	-25813
+▁fandosirana	-25814
+▁federasiona	-25815
+▁fitsidihana	-25816
+▁handraisana	-25817
+▁jaboticabal	-25818
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+▁liberiensis	-25820
+▁mahavokatra	-25821
+▁miantehitra	-25822
+▁mozambikana	-25823
+▁nifanohitra	-25824
+▁pedaliaceae	-25825
+▁repoblikana	-25826
+▁tsindrimpeo	-25827
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+▁mahasamihafa	-25834
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+▁nohamafisina	-25839
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+▁andriamanjato	-25841
+▁asaramantsina	-25842
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+▁fanavakavaham	-25846
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+▁tendrombohitr	-25851
+▁mifindrafindra	-25852
+▁nampitondraina	-25853
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+▁bagrat	-26458
+▁barôka	-26459
+▁basket	-26460
+▁beloha	-26461
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+▁billom	-26464
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+▁calder	-26468
+▁cancer	-26469
+▁chabot	-26470
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+▁gigant	-26499
+▁goavam	-26500
+▁grover	-26501
+▁gôrila	-26502
+▁hamaly	-26503
+▁hertha	-26504
+▁hirika	-26505
+▁hochst	-26506
+▁husayn	-26507
+▁invest	-26508
+▁ipetra	-26509
+▁jamnia	-26510
+▁justus	-26511
+▁kalaka	-26512
+▁kanôna	-26513
+▁karpat	-26514
+▁kassel	-26515
+▁lamine	-26516
+▁laurel	-26517
+▁lauren	-26518
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+▁libert	-26520
+▁linksa	-26521
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+▁loyola	-26523
+▁mahefa	-26524
+▁majika	-26525
+▁mallet	-26526
+▁malpig	-26527
+▁mampam	-26528
+▁manoro	-26529
+▁marais	-26530
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+▁masada	-26532
+▁master	-26533
+▁mifoha	-26534
+▁mimoso	-26535
+▁modibo	-26536
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+▁montél	-26538
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+▁munich	-26540
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+▁narbon	-26543
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+▁nofino	-26547
+▁noresa	-26548
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+▁oigora	-26550
+▁palmar	-26551
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+▁parlem	-26553
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+▁pawnee	-26555
+▁pirita	-26556
+▁planch	-26557
+▁platyr	-26558
+▁pombal	-26559
+▁portal	-26560
+▁prunay	-26561
+▁rafohy	-26562
+▁regist	-26563
+▁rigaud	-26564
+▁rights	-26565
+▁romero	-26566
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+▁royère	-26568
+▁régine	-26569
+▁sagart	-26570
+▁sahrul	-26571
+▁salman	-26572
+▁sander	-26573
+▁sanger	-26574
+▁saraha	-26575
+▁sibree	-26576
+▁sivana	-26577
+▁sohika	-26578
+▁soleda	-26579
+▁sommer	-26580
+▁sufyan	-26581
+▁suidae	-26582
+▁superc	-26583
+▁suárez	-26584
+▁tabriz	-26585
+▁tanief	-26586
+▁taovan	-26587
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+▁tiktok	-26590
+▁tringa	-26591
+▁tromba	-26592
+▁tsiron	-26593
+▁tucson	-26594
+▁tànana	-26595
+▁vahona	-26596
+▁valano	-26597
+▁vanobe	-26598
+▁verona	-26599
+▁watten	-26600
+▁économ	-26601
+▁ôfisia	-26602
+angatsia	-26603
+anianana	-26604
+arenberg	-26605
+beaumont	-26606
+botswana	-26607
+cabardès	-26608
+carignan	-26609
+cephalus	-26610
+consulté	-26611
+division	-26612
+emperora	-26613
+ignolles	-26614
+iôgrafia	-26615
+mbadiany	-26616
+mpilalao	-26617
+ombohana	-26618
+piaraham	-26619
+thaurion	-26620
+uderdale	-26621
+zizenina	-26622
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+ôliniôma	-26624
+▁aguirre	-26625
+▁aimorés	-26626
+▁ambatom	-26627
+▁ambatry	-26628
+▁ambohij	-26629
+▁ambondo	-26630
+▁antisem	-26631
+▁aoriany	-26632
+▁asorotà	-26633
+▁atodina	-26634
+▁avadika	-26635
+▁barnabà	-26636
+▁barreto	-26637
+▁benedic	-26638
+▁burbank	-26639
+▁caracas	-26640
+▁caracci	-26641
+▁colonia	-26642
+▁coronel	-26643
+▁coutach	-26644
+▁cyrille	-26645
+▁desvres	-26646
+▁eleanor	-26647
+▁esteban	-26648
+▁eugenio	-26649
+▁fahefam	-26650
+▁fahizay	-26651
+▁fanavao	-26652
+▁feniksa	-26653
+▁fiasana	-26654
+▁freitas	-26655
+▁fresnoy	-26656
+▁genghis	-26657
+▁gennaro	-26658
+▁ghebret	-26659
+▁guillet	-26660
+▁gémozac	-26661
+▁haizina	-26662
+▁hartley	-26663
+▁heliôma	-26664
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+▁horonam	-26666
+▁hubbard	-26667
+▁humaitá	-26668
+▁iberika	-26669
+▁ignacio	-26670
+▁ignazio	-26671
+▁isandra	-26672
+▁jeanine	-26673
+▁jentily	-26674
+▁jiménez	-26675
+▁kalitao	-26676
+▁kambavy	-26677
+▁karpaty	-26678
+▁karthli	-26679
+▁korzety	-26680
+▁leandri	-26681
+▁library	-26682
+▁listrin	-26683
+▁litiôma	-26684
+▁lumière	-26685
+▁mahafao	-26686
+▁manipur	-26687
+▁mariyah	-26688
+▁matotra	-26689
+▁matsiro	-26690
+▁mayenne	-26691
+▁maymuna	-26692
+▁moderne	-26693
+▁mozikam	-26694
+▁mpanefy	-26695
+▁mpanova	-26696
+▁nakambé	-26697
+▁nananan	-26698
+▁naongan	-26699
+▁natural	-26700
+▁neufchâ	-26701
+▁nogaret	-26702
+▁nouveau	-26703
+▁panente	-26704
+▁pascale	-26705
+▁pentina	-26706
+▁picasso	-26707
+▁pirinty	-26708
+▁polillo	-26709
+▁porcien	-26710
+▁porcula	-26711
+▁premier	-26712
+▁ratsira	-26713
+▁ritchie	-26714
+▁roussel	-26715
+▁sakaibe	-26716
+▁salamon	-26717
+▁samoina	-26718
+▁senador	-26719
+▁statist	-26720
+▁strozzi	-26721
+▁taksôna	-26722
+▁tatitry	-26723
+▁tompoko	-26724
+▁torkana	-26725
+▁trôpika	-26726
+▁turnera	-26727
+▁valpara	-26728
+▁voabodo	-26729
+▁voaniho	-26730
+▁webster	-26731
+cheophyta	-26732
+ikambanan	-26733
+imakirana	-26734
+indianina	-26735
+kandriana	-26736
+madeleine	-26737
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+ontoloana	-26739
+pahoviana	-26740
+sembanana	-26741
+siatsiaka	-26742
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+sylvicola	-26744
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+vingeanne	-26747
+voalohany	-26748
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+ôrtôdôksa	-26750
+▁ambinany	-26751
+▁amontana	-26752
+▁andersen	-26753
+▁antidahy	-26754
+▁aostrala	-26755
+▁archives	-26756
+▁bantôida	-26757
+▁bellevue	-26758
+▁bousquet	-26759
+▁bragança	-26760
+▁business	-26761
+▁democrát	-26762
+▁einstein	-26763
+▁ekinôksa	-26764
+▁fairview	-26765
+▁families	-26766
+▁famoahan	-26767
+▁fanahiny	-26768
+▁fanorona	-26769
+▁fantatro	-26770
+▁fehizoro	-26771
+▁fihanaky	-26772
+▁fijeriny	-26773
+▁filozofa	-26774
+▁fisandra	-26775
+▁fitaovan	-26776
+▁fotoanan	-26777
+▁freiburg	-26778
+▁gilberto	-26779
+▁goavambe	-26780
+▁hahazoan	-26781
+▁hanafaka	-26782
+▁hanamora	-26783
+▁hathaway	-26784
+▁hispania	-26785
+▁hitoetra	-26786
+▁hôlmiôma	-26787
+▁ianarana	-26788
+▁ivaiporã	-26789
+▁johnston	-26790
+▁kakhétie	-26791
+▁kananita	-26792
+▁karthala	-26793
+▁kingston	-26794
+▁mameloka	-26795
+▁mireille	-26796
+▁misakana	-26797
+▁moramora	-26798
+▁morarano	-26799
+▁mpandalo	-26800
+▁mpihinan	-26801
+▁mpisoron	-26802
+▁mônazita	-26803
+▁nanamora	-26804
+▁nandroba	-26805
+▁nangonin	-26806
+▁nanteuil	-26807
+▁neandert	-26808
+▁nianjera	-26809
+▁nihazona	-26810
+▁nolazain	-26811
+▁paulette	-26812
+▁peshitta	-26813
+▁pinochet	-26814
+▁rosières	-26815
+▁sarangan	-26816
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+▁schröder	-26818
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+▁sinagôga	-26820
+▁sjöstedt	-26821
+▁stanford	-26822
+▁tanalahy	-26823
+▁tantanan	-26824
+▁traktera	-26825
+▁tsindrin	-26826
+▁ulmaceae	-26827
+▁visigôty	-26828
+▁vokovoko	-26829
+▁volasira	-26830
+▁waldemar	-26831
+▁zabolôna	-26832
+▁zambézia	-26833
+analamanga	-26834
+mpanoratra	-26835
+oldenbourg	-26836
+pifohazana	-26837
+ôrtôdôksia	-26838
+▁acquaviva	-26839
+▁adansonia	-26840
+▁agapornis	-26841
+▁amboanala	-26842
+▁antoandro	-26843
+▁artemisia	-26844
+▁atlántico	-26845
+▁baldassar	-26846
+▁balthazar	-26847
+▁barnabasy	-26848
+▁bartolomé	-26849
+▁bernieria	-26850
+▁biodivers	-26851
+▁boliviana	-26852
+▁camembert	-26853
+▁cantabria	-26854
+▁champigny	-26855
+▁cornelisz	-26856
+▁cézallier	-26857
+▁dieulefit	-26858
+▁dipsaceus	-26859
+▁esperança	-26860
+▁establish	-26861
+▁fairfield	-26862
+▁fanakonam	-26863
+▁fanjifana	-26864
+▁ferrières	-26865
+▁fiarahana	-26866
+▁fifankaha	-26867
+▁filaminam	-26868
+▁fivarotan	-26869
+▁fôrmôzana	-26870
+▁haifiteny	-26871
+▁haikoriam	-26872
+▁hasideana	-26873
+▁hôlôferna	-26874
+▁inôkentio	-26875
+▁johansson	-26876
+▁joinville	-26877
+▁kominista	-26878
+▁latifolia	-26879
+▁lignières	-26880
+▁lombardia	-26881
+▁manjavona	-26882
+▁milatsaka	-26883
+▁mitsidika	-26884
+▁mussolini	-26885
+▁nabokôdôn	-26886
+▁nahatsapa	-26887
+▁nankalaza	-26888
+▁natahotra	-26889
+▁newcastle	-26890
+▁nianarany	-26891
+▁niorenany	-26892
+▁nogentais	-26893
+▁nohajaina	-26894
+▁nolazaina	-26895
+▁oleksandr	-26896
+▁sakamalao	-26897
+▁soatanàna	-26898
+▁stephanie	-26899
+▁stôikiana	-26900
+▁supérieur	-26901
+▁tanimatin	-26902
+▁tôkariana	-26903
+▁valcezard	-26904
+▁varavaran	-26905
+▁voakasika	-26906
+▁wuppertal	-26907
+▁zanatanin	-26908
+pifidianana	-26909
+▁ambohimana	-26910
+▁ambondrona	-26911
+▁andriamani	-26912
+▁ankohonany	-26913
+▁atsinanany	-26914
+▁australian	-26915
+▁autonomous	-26916
+▁beauregard	-26917
+▁bridgeport	-26918
+▁champenois	-26919
+▁compostela	-26920
+▁cordillera	-26921
+▁episkôpaly	-26922
+▁fahampiana	-26923
+▁fandiovana	-26924
+▁fiangonany	-26925
+▁fifankatia	-26926
+▁greenville	-26927
+▁guanajuato	-26928
+▁hanampiana	-26929
+▁hieronymus	-26930
+▁historique	-26931
+▁hitondrana	-26932
+▁hutchinson	-26933
+▁iogoslavia	-26934
+▁management	-26935
+▁manantitra	-26936
+▁mangotraka	-26937
+▁maroserana	-26938
+▁menarandra	-26939
+▁mizarazara	-26940
+▁monisipaly	-26941
+▁mouthoumet	-26942
+▁natsangany	-26943
+▁nikôdemôsy	-26944
+▁nipetrahan	-26945
+▁nitandrina	-26946
+▁nogadraina	-26947
+▁noheveriny	-26948
+▁notokanana	-26949
+▁orogoaiana	-26950
+▁patriarika	-26951
+▁patrocínio	-26952
+▁preterisma	-26953
+▁providence	-26954
+▁rakotondra	-26955
+▁sisintanin	-26956
+▁sundamomum	-26957
+▁sôsialisma	-26958
+▁voninahitr	-26959
+morontsiraka	-26960
+pandrenesana	-26961
+tarehimarika	-26962
+▁aleksandrov	-26963
+▁ambodimanga	-26964
+▁ampahefatry	-26965
+▁antrôpôlôga	-26966
+▁chamberlain	-26967
+▁conselheiro	-26968
+▁disprôsiôma	-26969
+▁fahambonian	-26970
+▁fampianaram	-26971
+▁fampihenana	-26972
+▁fampimirana	-26973
+▁faravohitra	-26974
+▁fihetsehana	-26975
+▁fiombonambe	-26976
+▁fivoriamben	-26977
+▁gadôliniôma	-26978
+▁jeôpôlitika	-26979
+▁milenarisma	-26980
+▁mullerornis	-26981
+▁nanandratra	-26982
+▁natoralisma	-26983
+▁nympheaceae	-26984
+▁pentecostal	-26985
+▁protopterus	-26986
+▁tsinjoarivo	-26987
+▁villamblard	-26988
+▁zanabintana	-26989
+pitondrantena	-26990
+▁andriantsoly	-26991
+▁antenantenan	-26992
+▁antsahadinta	-26993
+▁braunschweig	-26994
+▁broadcasting	-26995
+▁construction	-26996
+▁fahatanorany	-26997
+▁fitandremana	-26998
+▁linguistique	-26999
+▁manarakaraka	-27000
+▁manelanelana	-27001
+▁rakotomalala	-27002
+▁revôlisiônan	-27003
+▁streptopelia	-27004
+▁afindrafindra	-27005
+▁alexandrovich	-27006
+▁aostralianina	-27007
+▁epistemôlôjia	-27008
+▁fahasambarana	-27009
+▁fanapoizinana	-27010
+▁kônfosianisma	-27011
+▁kôngregasiôna	-27012
+▁mathématiques	-27013
+▁mpanoradalàna	-27014
+▁neufchâtelois	-27015
+▁sambiranensis	-27016
+▁fampandehanana	-27017
+▁fanatontoloana	-27018
+▁fieritreretana	-27019
+▁mihetsiketsika	-27020
+▁mpampihorohoro	-27021
+▁mpiandraikitra	-27022
+▁cryptosylvicola	-27023
+/)	-27024
+mâ	-27025
+pc	-27026
+vp	-27027
+vá	-27028
+zō	-27029
+ôy	-27030
+ри	-27031
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+بل	-27033
+يا	-27034
+▁ā	-27035
+▁ו	-27036
+bau	-27037
+cek	-27038
+cox	-27039
+coy	-27040
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+oku	-27060
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+psd	-27064
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+íra	-27077
+ānī	-27078
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+יהו	-27083
+▁->	-27084
+▁aç	-27085
+▁cj	-27086
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+▁fd	-27089
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+▁jt	-27091
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+ctus	-27117
+célé	-27118
+deka	-27119
+dera	-27120
+dish	-27121
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+▁benghalensis	-28185
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+▁tesalia	-39180
+▁tetenin	-39181
+▁theotok	-39182
+▁tiatîra	-39183
+▁tombola	-39184
+▁tongoza	-39185
+▁toronto	-39186
+▁travers	-39187
+▁tucuman	-39188
+▁uffried	-39189
+▁valença	-39190
+▁vernoux	-39191
+▁vicomte	-39192
+▁voajana	-39193
+▁voavoly	-39194
+▁wurdack	-39195
+▁zambezi	-39196
+▁zealand	-39197
+▁zizania	-39198
+ambositra	-39199
+aostralia	-39200
+arakaraka	-39201
+aubespine	-39202
+dampierre	-39203
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+espaniôla	-39206
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+hasparren	-39208
+imisaraka	-39209
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+manakaiky	-39213
+mpisorona	-39214
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+vicdessos	-39219
+vondronan	-39220
+▁académie	-39221
+▁agostini	-39222
+▁ambalabe	-39223
+▁amboadia	-39224
+▁ambohiby	-39225
+▁amerinda	-39226
+▁ampiasan	-39227
+▁ampivoan	-39228
+▁anatidae	-39229
+▁andoavam	-39230
+▁antipapa	-39231
+▁antonius	-39232
+▁antsoiny	-39233
+▁appendic	-39234
+▁ardasira	-39235
+▁arentèle	-39236
+▁artigues	-39237
+▁audunois	-39238
+▁avesnois	-39239
+▁azadirak	-39240
+▁bacteria	-39241
+▁baltasar	-39242
+▁bermioda	-39243
+▁bodensee	-39244
+▁bogusław	-39245
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+▁borondey	-39247
+▁brittany	-39248
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+▁cabannes	-39250
+▁caerulea	-39251
+▁canberra	-39252
+▁caprimul	-39253
+▁carteret	-39254
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+▁castanet	-39256
+▁castello	-39257
+▁changwat	-39258
+▁charlton	-39259
+▁crassula	-39260
+▁dadatoan	-39261
+▁delaware	-39262
+▁demôtika	-39263
+▁dionycha	-39264
+▁division	-39265
+▁división	-39266
+▁djibouti	-39267
+▁dorothée	-39268
+▁dubreuil	-39269
+▁dôlômita	-39270
+▁edgerton	-39271
+▁electron	-39272
+▁emeraoda	-39273
+▁estadual	-39274
+▁euclides	-39275
+▁ezequiel	-39276
+▁faingana	-39277
+▁famelana	-39278
+▁famonjen	-39279
+▁fanehoam	-39280
+▁fanjakam	-39281
+▁faralahy	-39282
+▁fasehana	-39283
+▁fenerive	-39284
+▁fihoaram	-39285
+▁fiitatry	-39286
+▁filioque	-39287
+▁floresta	-39288
+▁fototara	-39289
+▁foucault	-39290
+▁freeport	-39291
+▁freetown	-39292
+▁gherardi	-39293
+▁gueugnon	-39294
+▁générale	-39295
+▁gévaudan	-39296
+▁hafahafa	-39297
+▁hahamora	-39298
+▁halalina	-39299
+▁hannibal	-39300
+▁haoaiana	-39301
+▁hardware	-39302
+▁haviland	-39303
+▁hazolahy	-39304
+▁henschel	-39305
+▁hiankina	-39306
+▁hiatrika	-39307
+▁hidirany	-39308
+▁hofidina	-39309
+▁hosokawa	-39310
+▁huguette	-39311
+▁imailaka	-39312
+▁indridae	-39313
+▁indrinda	-39314
+▁indépend	-39315
+▁inefatra	-39316
+▁informat	-39317
+▁ishihara	-39318
+▁jeannine	-39319
+▁jebosita	-39320
+▁jennings	-39321
+▁jermaine	-39322
+▁jermania	-39323
+▁jeôlôjia	-39324
+▁kaisaria	-39325
+▁kaligola	-39326
+▁kapohina	-39327
+▁kapreôlo	-39328
+▁karijita	-39329
+▁khanukka	-39330
+▁kianteny	-39331
+▁klôriora	-39332
+▁komnenos	-39333
+▁koonterm	-39334
+▁kôlibria	-39335
+▁labrador	-39336
+▁lakolosy	-39337
+▁lalandra	-39338
+▁larroque	-39339
+▁larvatus	-39340
+▁lassalle	-39341
+▁laôdikia	-39342
+▁laôdisea	-39343
+▁lehibebe	-39344
+▁levitika	-39345
+▁lewiston	-39346
+▁lexpress	-39347
+▁longueil	-39348
+▁magellan	-39349
+▁mahavelo	-39350
+▁maitland	-39351
+▁malaizia	-39352
+▁malesita	-39353
+▁manafaka	-39354
+▁mandrava	-39355
+▁manindry	-39356
+▁manomana	-39357
+▁mccarthy	-39358
+▁melastom	-39359
+▁mercator	-39360
+▁mikatona	-39361
+▁miramont	-39362
+▁misiones	-39363
+▁mokonazy	-39364
+▁monmouth	-39365
+▁morville	-39366
+▁mpifanao	-39367
+▁murakami	-39368
+▁mônarsia	-39369
+▁nahalasa	-39370
+▁nahitany	-39371
+▁nanatona	-39372
+▁natolotr	-39373
+▁nefilima	-39374
+▁nihamaro	-39375
+▁nilaozan	-39376
+▁nofaizin	-39377
+▁nolavina	-39378
+▁nolovana	-39379
+▁nonenany	-39380
+▁norberto	-39381
+▁noterena	-39382
+▁numenius	-39383
+▁nérondes	-39384
+▁oantitsy	-39385
+▁osbourne	-39386
+▁palacios	-39387
+▁pasquale	-39388
+▁pentekot	-39389
+▁perrière	-39390
+▁peterson	-39391
+▁petrović	-39392
+▁petrucci	-39393
+▁pimentel	-39394
+▁porecatu	-39395
+▁prachuap	-39396
+▁prospect	-39397
+▁prôtista	-39398
+▁raimondo	-39399
+▁ravahiny	-39400
+▁ravitoto	-39401
+▁refleksa	-39402
+▁roberval	-39403
+▁rockford	-39404
+▁roebling	-39405
+▁rondonia	-39406
+▁rômantsa	-39407
+▁sahidika	-39408
+▁salvetat	-39409
+▁sarisary	-39410
+▁savannah	-39411
+▁scorsese	-39412
+▁seigneur	-39413
+▁seleokia	-39414
+▁selongey	-39415
+▁sheridan	-39416
+▁simpansy	-39417
+▁sinôdaly	-39418
+▁sondaney	-39419
+▁spéciale	-39420
+▁suleiman	-39421
+▁svensson	-39422
+▁sôlstisy	-39423
+▁tanimaty	-39424
+▁teritery	-39425
+▁tetiaran	-39426
+▁thurston	-39427
+▁tibetika	-39428
+▁toddalia	-39429
+▁torkaman	-39430
+▁torvalds	-39431
+▁toyotomi	-39432
+▁trentino	-39433
+▁tsodrano	-39434
+▁tôkôisma	-39435
+▁vaillant	-39436
+▁vakhtang	-39437
+▁venezoel	-39438
+▁victorin	-39439
+▁villegas	-39440
+▁voakasik	-39441
+▁volovolo	-39442
+▁vonenina	-39443
+▁wilfried	-39444
+▁windhoek	-39445
+▁yaroslav	-39446
+▁zbigniew	-39447
+ampiharina	-39448
+architecte	-39449
+ikeniarivo	-39450
+invilliers	-39451
+iveniarivo	-39452
+kilahimena	-39453
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+mpikambana	-39455
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+renivohitr	-39458
+tanterahan	-39459
+tsanganana	-39460
+vermandois	-39461
+▁abaribary	-39462
+▁agostinho	-39463
+▁ahalalana	-39464
+▁albigeois	-39465
+▁alcántara	-39466
+▁algônkina	-39467
+▁alnéloise	-39468
+▁alominina	-39469
+▁alzasiana	-39470
+▁ampanjaka	-39471
+▁anadahiny	-39472
+▁anarsisma	-39473
+▁andramena	-39474
+▁andrasana	-39475
+▁anombohan	-39476
+▁araripina	-39477
+▁ardennais	-39478
+▁aristôtel	-39479
+▁asparagus	-39480
+▁augustine	-39481
+▁ayutthaya	-39482
+▁bagration	-39483
+▁bartelemy	-39484
+▁beersheba	-39485
+▁blackfeet	-39486
+▁brachyura	-39487
+▁bronisław	-39488
+▁burkhardt	-39489
+▁carluxais	-39490
+▁charenton	-39491
+▁chaudenay	-39492
+▁comminges	-39493
+▁confedera	-39494
+▁contarini	-39495
+▁corrézien	-39496
+▁coulibaly	-39497
+▁couturier	-39498
+▁covington	-39499
+▁diatônika	-39500
+▁domanović	-39501
+▁ekôlôjika	-39502
+▁elliptica	-39503
+▁engelbert	-39504
+▁entertain	-39505
+▁esperanto	-39506
+▁fahalalan	-39507
+▁fahazoany	-39508
+▁falklands	-39509
+▁fanamiana	-39510
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+▁fanemotra	-39512
+▁feldspata	-39513
+▁feuillade	-39514
+▁fiakarany	-39515
+▁fiarahany	-39516
+▁fifanandr	-39517
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+▁filipiana	-39520
+▁fiomanana	-39521
+▁fitaomana	-39522
+▁fitetezam	-39523
+▁fitoviany	-39524
+▁fontaines	-39525
+▁frankfort	-39526
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+▁gallinula	-39529
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+▁hamoahana	-39532
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+▁hovonoina	-39542
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+▁ikambanan	-39544
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+▁izaitsizy	-39546
+▁kerintôsy	-39547
+▁kongresin	-39548
+▁kôirabôrô	-39549
+▁kôlôsiana	-39550
+▁magmatika	-39551
+▁mahasoabe	-39552
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+▁mamintina	-39554
+▁mampanahy	-39555
+▁manefitra	-39556
+▁mangaliba	-39557
+▁mankahala	-39558
+▁maripanan	-39559
+▁marksisma	-39560
+▁masianaka	-39561
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+▁mccartney	-39563
+▁mcconnell	-39564
+▁middleton	-39565
+▁mihemotra	-39566
+▁mitaraina	-39567
+▁monotypic	-39568
+▁movimento	-39569
+▁mpifanila	-39570
+▁nanakiana	-39571
+▁nanjanaka	-39572
+▁natomboky	-39573
+▁niakarany	-39574
+▁niantsoan	-39575
+▁nicaragua	-39576
+▁nifandona	-39577
+▁niharatsy	-39578
+▁nisarahan	-39579
+▁nisoratra	-39580
+▁nomidiana	-39581
+▁northwest	-39582
+▁olimpikan	-39583
+▁pangalana	-39584
+▁peroviana	-39585
+▁petroleum	-39586
+▁plantagen	-39587
+▁polynésie	-39588
+▁porphyrio	-39589
+▁prionitis	-39590
+▁rakotovao	-39591
+▁ratcliffe	-39592
+▁ravimbony	-39593
+▁relations	-39594
+▁roalahiny	-39595
+▁rosenberg	-39596
+▁samarkand	-39597
+▁samouelle	-39598
+▁schomberg	-39599
+▁sinograma	-39600
+▁sitrinina	-39601
+▁somatrana	-39602
+▁soulaines	-39603
+▁tambanosy	-39604
+▁taminareo	-39605
+▁taranjany	-39606
+▁tarantino	-39607
+▁terebinth	-39608
+▁tohadrano	-39609
+▁trencavel	-39610
+▁tsimalomo	-39611
+▁tsirivavy	-39612
+▁vaccinium	-39613
+▁vaomieran	-39614
+▁variegata	-39615
+▁venaissin	-39616
+▁voakasiky	-39617
+▁vontoatin	-39618
+antsinanana	-39619
+cornouaille	-39620
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+imampianina	-39622
+information	-39623
+itsakitsaka	-39624
+mboninolona	-39625
+openedition	-39626
+pahatongany	-39627
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+▁abyssinica	-39629
+▁akadianina	-39630
+▁alyaksandr	-39631
+▁anabatisma	-39632
+▁andevohova	-39633
+▁andraisana	-39634
+▁ankabiazan	-39635
+▁ankatoavin	-39636
+▁ankizivavy	-39637
+▁antanetibe	-39638
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+▁antehiroka	-39640
+▁antsingeny	-39641
+▁archambaud	-39642
+▁arthropoda	-39643
+▁astérienne	-39644
+▁bainbridge	-39645
+▁bartholoma	-39646
+▁basketball	-39647
+▁belledonne	-39648
+▁bellefonds	-39649
+▁beroberoka	-39650
+▁birkenfeld	-39651
+▁blockchain	-39652
+▁cassavetes	-39653
+▁celebensis	-39654
+▁cleomaceae	-39655
+▁collection	-39656
+▁combraille	-39657
+▁demografia	-39658
+▁devanagari	-39659
+▁eoklidiana	-39660
+▁epikorisma	-39661
+▁fahadisoam	-39662
+▁faharetany	-39663
+▁famafazana	-39664
+▁fametraham	-39665
+▁fanakanana	-39666
+▁fanantenam	-39667
+▁fanolanana	-39668
+▁fanondrana	-39669
+▁fanovanana	-39670
+▁fanovonana	-39671
+▁fibaikoana	-39672
+▁fikapohana	-39673
+▁fikarohany	-39674
+▁firotsahan	-39675
+▁fivelomany	-39676
+▁floribunda	-39677
+▁fluminense	-39678
+▁guggenheim	-39679
+▁haliaeetus	-39680
+▁hampihatra	-39681
+▁hanaisotra	-39682
+▁hanazavana	-39683
+▁harmonious	-39684
+▁hazokesika	-39685
+▁heidenheim	-39686
+▁henôteisma	-39687
+▁hitambatra	-39688
+▁hitaterana	-39689
+▁hitazonana	-39690
+▁hivarinany	-39691
+▁homamiadan	-39692
+▁itapetinga	-39693
+▁karpatiana	-39694
+▁katedralin	-39695
+▁katsatsaka	-39696
+▁keratinina	-39697
+▁kilahivavy	-39698
+▁kohgīlūyeh	-39699
+▁kœnigsmark	-39700
+▁lanceolata	-39701
+▁libreville	-39702
+▁louisville	-39703
+▁manandrana	-39704
+▁mandositra	-39705
+▁mandragora	-39706
+▁mandrahona	-39707
+▁marysville	-39708
+▁matheysine	-39709
+▁miantraika	-39710
+▁mibaribary	-39711
+▁mivangongo	-39712
+▁mpanatrika	-39713
+▁mpisehatra	-39714
+▁nametrahan	-39715
+▁nampitaina	-39716
+▁nanaporofo	-39717
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+▁nanesorana	-39719
+▁naucellois	-39720
+▁neufchâtel	-39721
+▁nianjadian	-39722
+▁niforonany	-39723
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+▁nosokajina	-39725
+▁paniculata	-39726
+▁patrimoine	-39727
+▁pellegrini	-39728
+▁penthièvre	-39729
+▁persianina	-39730
+▁phonétique	-39731
+▁plasmodium	-39732
+▁praetorius	-39733
+▁procaccini	-39734
+▁protestant	-39735
+▁puducherry	-39736
+▁rhizophora	-39737
+▁salicaceae	-39738
+▁solontenam	-39739
+▁sutherland	-39740
+▁taksônômia	-39741
+▁tamaulipas	-39742
+▁tanzaniana	-39743
+▁teôkratika	-39744
+▁thalasseus	-39745
+▁thironnais	-39746
+▁tsimbazaza	-39747
+▁varangiana	-39748
+▁voalahatra	-39749
+▁volahavana	-39750
+▁watchtower	-39751
+▁wikivoyage	-39752
+▁zervanisma	-39753
+enseignement	-39754
+palestiniana	-39755
+pampianarany	-39756
+panamboarana	-39757
+▁amboarampeo	-39758
+▁ambohidrano	-39759
+▁ampanenoina	-39760
+▁andranovory	-39761
+▁andrianjafy	-39762
+▁ankaranense	-39763
+▁antibiotika	-39764
+▁antsinanany	-39765
+▁arpajonnais	-39766
+▁beckenbauer	-39767
+▁bischwiller	-39768
+▁bouthillier	-39769
+▁bôgômilisma	-39770
+▁caesalpinia	-39771
+▁castiglione	-39772
+▁centerville	-39773
+▁christensen	-39774
+▁châtaignier	-39775
+▁clarksville	-39776
+▁demografika	-39777
+▁département	-39778
+▁ekiomenikan	-39779
+▁etymologies	-39780
+▁eurofighter	-39781
+▁fahavaratry	-39782
+▁fahazotoana	-39783
+▁fampidinana	-39784
+▁fankatoavan	-39785
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+▁fitsaharana	-39787
+▁fransiskana	-39788
+▁hanambaràna	-39789
+▁heliôpôlisy	-39790
+▁hylobatidae	-39791
+▁inkizisiôna	-39792
+▁karbônifera	-39793
+▁lahatsoratr	-39794
+▁leguminosae	-39795
+▁loksamborga	-39796
+▁madiotanana	-39797
+▁maisonneuve	-39798
+▁manasitrana	-39799
+▁maromiandra	-39800
+▁mielanelana	-39801
+▁mifampitohy	-39802
+▁mikorontana	-39803
+▁mpampiofana	-39804
+▁mussidanais	-39805
+▁nahandroina	-39806
+▁nampifandra	-39807
+▁nandefasana	-39808
+▁ophioglossa	-39809
+▁pauciflorus	-39810
+▁perestroika	-39811
+▁pyramidalis	-39812
+▁pôlikarpôsy	-39813
+▁pôntifikaly	-39814
+▁rémalardais	-39815
+▁sagittarius	-39816
+▁teôlôgomena	-39817
+▁tragelaphus	-39818
+▁voarohirohy	-39819
+▁accipitridae	-39820
+▁adriamanitra	-39821
+▁afrôaziatika	-39822
+▁ambasadaoron	-39823
+▁ambodiampana	-39824
+▁andrimanitra	-39825
+▁apôlinariôsy	-39826
+▁bartholomeus	-39827
+▁chénérailles	-39828
+▁curvirostris	-39829
+▁dionarintany	-39830
+▁encyclopédie	-39831
+▁fahamboniana	-39832
+▁fampanjakana	-39833
+▁fampitoviana	-39834
+▁fanalefahana	-39835
+▁fanondrahana	-39836
+▁fayetteville	-39837
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+▁handrefesana	-39840
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+▁ifandraisana	-39843
+▁khorramshahr	-39844
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+▁literatioran	-39846
+▁mademoiselle	-39847
+▁mahafalensis	-39848
+▁manavakavaka	-39849
+▁mandatehezam	-39850
+▁marckolsheim	-39851
+▁miankavanana	-39852
+▁mijoalajoala	-39853
+▁nampamonoiny	-39854
+▁nianavaratra	-39855
+▁nodimbiasany	-39856
+▁nohatsaraina	-39857
+▁parafiletika	-39858
+▁pelagianisma	-39859
+▁portulacaria	-39860
+▁ravelonarivo	-39861
+▁tombokavatsa	-39862
+▁tombontsoany	-39863
+▁vatofantsika	-39864
+▁zazamarolahy	-39865
+▁brouvelieures	-39866
+▁christianisme	-39867
+▁fanelanelanan	-39868
+▁fanjakazakany	-39869
+▁fankaherezana	-39870
+▁fisafidianana	-39871
+▁fitsikilovana	-39872
+▁fitsingerenan	-39873
+▁hampifanaraka	-39874
+▁hazofijaliana	-39875
+▁hidrôkarbiora	-39876
+▁lepilemuridae	-39877
+▁linguistiques	-39878
+▁mampifanaraka	-39879
+▁messerschmitt	-39880
+▁metrôpôlitana	-39881
+▁nampitambatra	-39882
+▁nieritreritra	-39883
+▁palaeognathae	-39884
+▁persiavahoaka	-39885
+▁rantsambatana	-39886
+▁tokamiantoana	-39887
+andrianakotrina	-39888
+▁aepyornithidae	-39889
+▁aleksandrovich	-39890
+▁andrianihoatra	-39891
+▁azadiraktinina	-39892
+▁castelroussine	-39893
+▁daubentoniidae	-39894
+▁fifanintsanana	-39895
+▁phoenicopterus	-39896
+▁pseodepigrafan	-39897
+▁razafimandimby	-39898
+▁tendrombohitry	-39899
+▁villefranchois	-39900
+▁andrianahilitsy	-39901
+▁fahatanterahana	-39902
+▁melastomataceae	-39903
+▁mivolombolamena	-39904
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+▁patriotique	-47296
+▁phasianidae	-47297
+▁phatthalung	-47298
+▁phitsanulok	-47299
+▁pseudalopex	-47300
+▁reconquista	-47301
+▁sabatariana	-47302
+▁sambofiaran	-47303
+▁samôgitiana	-47304
+▁sergeyevich	-47305
+▁siantifikan	-47306
+▁springsteen	-47307
+▁taksônômika	-47308
+▁tandindomim	-47309
+▁tanindrazan	-47310
+▁tanterakala	-47311
+▁tasalôniana	-47312
+▁technologie	-47313
+▁tongahasina	-47314
+▁tongologasy	-47315
+▁tsarasaotra	-47316
+▁utilisateur	-47317
+▁vakamiarina	-47318
+▁vasconcelos	-47319
+▁vatovandana	-47320
+▁województwo	-47321
+mboatsimarofy	-47322
+pisakafoanana	-47323
+▁ambodinonoka	-47324
+▁ambohimahazo	-47325
+▁ambohimasina	-47326
+▁ampasimazava	-47327
+▁analamahitsy	-47328
+▁brasiliensis	-47329
+▁chachoengsao	-47330
+▁communaupole	-47331
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+▁eklesiôlôjia	-47333
+▁fahamalinana	-47334
+▁faharinganan	-47335
+▁fahatezerana	-47336
+▁fahavelomana	-47337
+▁fahavononana	-47338
+▁famondronana	-47339
+▁fehinkevitra	-47340
+▁fermentation	-47341
+▁fouesnantais	-47342
+▁framasôneria	-47343
+▁governoratan	-47344
+▁hymenosicyos	-47345
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+▁isafidianana	-47347
+▁kilimandjaro	-47348
+▁konstantínos	-47349
+▁lakambazimba	-47350
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+▁mahafehitena	-47354
+▁maoritaniana	-47355
+▁metzdivision	-47356
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+▁mitandahatra	-47358
+▁mpampianatry	-47359
+▁nahafantaran	-47360
+▁neôpaganisma	-47361
+▁niantombohan	-47362
+▁ombalahivola	-47363
+▁petrakevitra	-47364
+▁ratsimamanga	-47365
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+▁soultzerland	-47368
+▁streptophyta	-47369
+▁tsarabanjina	-47370
+▁tsiatosidahy	-47371
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+▁vinanihefaka	-47374
+▁vinantolahin	-47375
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+andriamanibavy	-47378
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+▁amaranthaceae	-47380
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+▁malaimisaraka	-47389
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+▁niantsinanana	-47394
+▁nifampikasoka	-47395
+▁polytechnique	-47396
+▁pomeranianina	-47397
+▁rafenomanjato	-47398
+▁ratsimandrava	-47399
+▁razafimahaleo	-47400
+▁sianôbakteria	-47401
+▁soamanodidina	-47402
+▁spiritoalisma	-47403
+▁tahonanganala	-47404
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+▁amaryllidaceae	-47409
+▁ampifandraisin	-47410
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+▁andriamandresy	-47413
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+▁hippopotamidae	-47416
+▁kristadelfiana	-47417
+▁manarimbintana	-47418
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+▁tsiambanindahy	-47421
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+▁voahangindrano	-47423
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+▁françaises	-52565
+▁frontières	-52566
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+▁kabinetran	-52603
+▁kalinikosy	-52604
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+▁kôsmôgônia	-52607
+▁lautrecois	-52608
+▁leucocasia	-52609
+▁lewisville	-52610
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+▁randrianjo	-52664
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+▁tetiandron	-52692
+▁tetikasany	-52693
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+▁tinchebray	-52697
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+▁tshisekedi	-52700
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+▁antsamotady	-52742
+▁antsipirian	-52743
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+▁archambault	-52745
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+▁capparaceae	-52759
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+▁coudekerque	-52764
+▁countryball	-52765
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+▁fahandroana	-52769
+▁fahasahiran	-52770
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+▁fanjanahana	-52780
+▁fanompoambe	-52781
+▁fihandronan	-52782
+▁filmography	-52783
+▁filôzôfiany	-52784
+▁fipetrahana	-52785
+▁fisokajiana	-52786
+▁fitehirizan	-52787
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+▁fleischmann	-52790
+▁forcalquier	-52791
+▁fototarazon	-52792
+▁gainesville	-52793
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+▁hahaterahan	-52795
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+▁hanombohana	-52799
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+▁intercommun	-52802
+▁karibônetra	-52803
+▁lahatsorany	-52804
+▁laranjeiras	-52805
+▁lavidavitra	-52806
+▁lehimanjaka	-52807
+▁livingstone	-52808
+▁manapatrana	-52809
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+▁martinsburg	-52811
+▁metuliferus	-52812
+▁mihamitombo	-52813
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+▁tesalônisiana	-53009
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+▁tsekoslovakia	-53012
+▁tsienimbalala	-53013
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+λο	-53110
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+="+	-53128
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+▁maozôlean	-59274
+▁marimbona	-59275
+▁marosakoa	-59276
+▁martineau	-59277
+▁martorell	-59278
+▁martoulet	-59279
+▁masindray	-59280
+▁matsumoto	-59281
+▁mcdermott	-59282
+▁meleagris	-59283
+▁mennonite	-59284
+▁mercadier	-59285
+▁miantoana	-59286
+▁micrantha	-59287
+▁midianita	-59288
+▁milefitra	-59289
+▁mineralin	-59290
+▁misatroka	-59291
+▁mitambatr	-59292
+▁mitaratra	-59293
+▁mitifitra	-59294
+▁mitsangan	-59295
+▁mivonkina	-59296
+▁mojokerto	-59297
+▁mondragón	-59298
+▁monferran	-59299
+▁mousseaux	-59300
+▁mpamitaka	-59301
+▁mpandrava	-59302
+▁mpandrefy	-59303
+▁mpanondro	-59304
+▁mpitazona	-59305
+▁mucronata	-59306
+▁météorite	-59307
+▁mülhausen	-59308
+▁nafindran	-59309
+▁nagashima	-59310
+▁nahangona	-59311
+▁nakambany	-59312
+▁nalahatra	-59313
+▁nalatsaka	-59314
+▁namoahany	-59315
+▁nanapitra	-59316
+▁nanintona	-59317
+▁nankininy	-59318
+▁nanoheran	-59319
+▁nanombana	-59320
+▁nanosotra	-59321
+▁nanticoke	-59322
+▁natsofoka	-59323
+▁nifikitra	-59324
+▁nihatsara	-59325
+▁nihavitsy	-59326
+▁nisehoana	-59327
+▁nisehoany	-59328
+▁nitenenan	-59329
+▁nivoahany	-59330
+▁nobaboiny	-59331
+▁nohazaina	-59332
+▁nohidiana	-59333
+▁nopotehin	-59334
+▁normandia	-59335
+▁nosahanin	-59336
+▁nosoloiny	-59337
+▁noveborac	-59338
+▁oceanside	-59339
+▁paganista	-59340
+▁paramount	-59341
+▁persianan	-59342
+▁peruviana	-59343
+▁petsenega	-59344
+▁piramidan	-59345
+▁porofoina	-59346
+▁pritchard	-59347
+▁psilocybe	-59348
+▁quelimane	-59349
+▁ragueneau	-59350
+▁rajaofera	-59351
+▁rajerison	-59352
+▁randrenja	-59353
+▁rastafary	-59354
+▁ravinkazo	-59355
+▁reinhardt	-59356
+▁rembrandt	-59357
+▁renaldini	-59358
+▁reservoir	-59359
+▁richardis	-59360
+▁riverdale	-59361
+▁riverview	-59362
+▁roavolana	-59363
+▁romanenko	-59364
+▁rosenthal	-59365
+▁rotundata	-59366
+▁rougemont	-59367
+▁rousselet	-59368
+▁rubiaceae	-59369
+▁rupestris	-59370
+▁rushville	-59371
+▁ruwenzori	-59372
+▁réveillon	-59373
+▁saifuddin	-59374
+▁sakaguchi	-59375
+▁sakaleona	-59376
+▁salimbeni	-59377
+▁sankeriba	-59378
+▁santionan	-59379
+▁sarkôfazy	-59380
+▁satellite	-59381
+▁satornaly	-59382
+▁savigneux	-59383
+▁schreiber	-59384
+▁schönborn	-59385
+▁senegalia	-59386
+▁sepúlveda	-59387
+▁sfondrati	-59388
+▁sheffield	-59389
+▁shepherds	-59390
+▁silvestro	-59391
+▁singazija	-59392
+▁sirenaika	-59393
+▁sitranina	-59394
+▁situation	-59395
+▁soulanges	-59396
+▁southport	-59397
+▁spiridôna	-59398
+▁stapleton	-59399
+▁steinmetz	-59400
+▁sternberg	-59401
+▁streaming	-59402
+▁structure	-59403
+▁strychnos	-59404
+▁sôsiôlôga	-59405
+▁tadayoshi	-59406
+▁taimorona	-59407
+▁takahashi	-59408
+▁talanjona	-59409
+▁tallemant	-59410
+▁tantarain	-59411
+▁taolanaro	-59412
+▁tartarôsy	-59413
+▁tavakkoli	-59414
+▁tenatenan	-59415
+▁terestria	-59416
+▁teôkrasia	-59417
+▁theodoric	-59418
+▁theodorus	-59419
+▁thouvenot	-59420
+▁thuringia	-59421
+▁tibetanan	-59422
+▁tinamidae	-59423
+▁tipôlôjia	-59424
+▁tonnelier	-59425
+▁traitteur	-59426
+▁tribonaly	-59427
+▁trongatsy	-59428
+▁truffiers	-59429
+▁tsikirity	-59430
+▁tsindrano	-59431
+▁tsindrona	-59432
+▁tsipelana	-59433
+▁tsirkasia	-59434
+▁ulmifolia	-59435
+▁valentina	-59436
+▁valinteny	-59437
+▁vandières	-59438
+▁vanofotsy	-59439
+▁ventadour	-59440
+▁verdunois	-59441
+▁verenigde	-59442
+▁veyssière	-59443
+▁vieuville	-59444
+▁vitellius	-59445
+▁voaangona	-59446
+▁voahaingo	-59447
+▁voasaraka	-59448
+▁voasarona	-59449
+▁vrindavan	-59450
+▁vuillaume	-59451
+▁vulpecula	-59452
+▁watertown	-59453
+▁wiedemann	-59454
+▁willaerts	-59455
+▁williston	-59456
+▁woodville	-59457
+▁zafisambo	-59458
+▁zeorziana	-59459
+▁ôligarsia	-59460
+▁ôrdônansa	-59461
+▁ôstrôgôty	-59462
+anakalozana	-59463
+andrianjaka	-59464
+chantemerle	-59465
+diteratiora	-59466
+draharahany	-59467
+dralehilahy	-59468
+ilafikarivo	-59469
+ladioscorea	-59470
+makedôniana	-59471
+mariparitra	-59472
+melaneziana	-59473
+miarinarivo	-59474
+monographie	-59475
+métropolite	-59476
+okanangatra	-59477
+otyledoneae	-59478
+pahaveloman	-59479
+pandalinana	-59480
+réalisateur	-59481
+varimbazaha	-59482
+▁abaribarin	-59483
+▁acridoidea	-59484
+▁ahandroina	-59485
+▁albertelli	-59486
+▁aldrovandi	-59487
+▁alominiôma	-59488
+▁aléxandros	-59489
+▁ambalamana	-59490
+▁ambararata	-59491
+▁ambodivoan	-59492
+▁americanus	-59493
+▁ampahatelo	-59494
+▁ampangaina	-59495
+▁ampasimena	-59496
+▁andraikitr	-59497
+▁andrianaly	-59498
+▁anjahamana	-59499
+▁ankadikely	-59500
+▁antipatera	-59501
+▁antsointso	-59502
+▁anzoategui	-59503
+▁anzoátegui	-59504
+▁aotôsefaly	-59505
+▁apostolika	-59506
+▁appalaches	-59507
+▁apôstôliny	-59508
+▁aromaniana	-59509
+▁astronomie	-59510
+▁aubameyang	-59511
+▁açailândia	-59512
+▁bangladesa	-59513
+▁batesville	-59514
+▁beauchamps	-59515
+▁birthplace	-59516
+▁bodenstein	-59517
+▁boussières	-59518
+▁brachyurus	-59519
+▁brookville	-59520
+▁caespitosa	-59521
+▁camerarius	-59522
+▁carondelet	-59523
+▁chantraine	-59524
+▁chlidonias	-59525
+▁christelle	-59526
+▁chrétienne	-59527
+▁cinnamomum	-59528
+▁citriodora	-59529
+▁clusiaceae	-59530
+▁commercial	-59531
+▁comunidade	-59532
+▁copenhagen	-59533
+▁democratic	-59534
+▁demography	-59535
+▁demokratas	-59536
+▁diasistema	-59537
+▁dinnendahl	-59538
+▁dypsidinae	-59539
+▁déshérités	-59540
+▁economique	-59541
+▁ekôsistema	-59542
+▁engenheiro	-59543
+▁enterprise	-59544
+▁epikoreana	-59545
+▁etnôgrafia	-59546
+▁fahalemena	-59547
+▁famotorana	-59548
+▁fampidiram	-59549
+▁fanadiovan	-59550
+▁fanalahidy	-59551
+▁fananganan	-59552
+▁fanatsaran	-59553
+▁fandaminam	-59554
+▁fandiorano	-59555
+▁faninefany	-59556
+▁fanjakanao	-59557
+▁fankahalan	-59558
+▁federativa	-59559
+▁fiankinana	-59560
+▁fiatrehana	-59561
+▁fifandonan	-59562
+▁fifantohan	-59563
+▁fihodinany	-59564
+▁fihotsahan	-59565
+▁fikasihana	-59566
+▁fiketohana	-59567
+▁fiketrahan	-59568
+▁filatsahan	-59569
+▁finakaviam	-59570
+▁fioravanti	-59571
+▁fiorentino	-59572
+▁fisakanana	-59573
+▁fisokirana	-59574
+▁fitarainan	-59575
+▁fitenenany	-59576
+▁fitokonana	-59577
+▁fitroarana	-59578
+▁fitsaihana	-59579
+▁fitsimohan	-59580
+▁fivavahako	-59581
+▁fivelarany	-59582
+▁frédérique	-59583
+▁germantown	-59584
+▁gibioktety	-59585
+▁gnassingbé	-59586
+▁grandville	-59587
+▁granitique	-59588
+▁greensboro	-59589
+▁guidobaldo	-59590
+▁guillaumin	-59591
+▁géographie	-59592
+▁halehibeny	-59593
+▁hamelezana	-59594
+▁hanavotana	-59595
+▁handatsaka	-59596
+▁handresena	-59597
+▁handrindra	-59598
+▁handripaka	-59599
+▁hanomanana	-59600
+▁hantatiana	-59601
+▁hemiorchis	-59602
+▁hiparitaka	-59603
+▁hiverenany	-59604
+▁hivezivezy	-59605
+▁hoffenheim	-59606
+▁ialohavana	-59607
+▁iamblikôsy	-59608
+▁ianantsony	-59609
+▁ifanarahan	-59610
+▁initiative	-59611
+▁inoktitota	-59612
+▁insolindia	-59613
+▁itantarana	-59614
+▁jordaniana	-59615
+▁jôrdaniana	-59616
+▁kalvinisma	-59617
+▁kambojiana	-59618
+▁kapurthala	-59619
+▁kontinenta	-59620
+▁kristianin	-59621
+▁kônfesiôna	-59622
+▁kônfosiosy	-59623
+▁kôrdierita	-59624
+▁lagerstrom	-59625
+▁lamblardie	-59626
+▁lanouaille	-59627
+▁liberation	-59628
+▁litchfield	-59629
+▁literature	-59630
+▁lohateniny	-59631
+▁lukashenko	-59632
+▁maastricht	-59633
+▁macdougall	-59634
+▁mahasahana	-59635
+▁makhmalbaf	-59636
+▁mampametra	-59637
+▁mampihetsi	-59638
+▁mandahatra	-59639
+▁mandialaza	-59640
+▁mandronono	-59641
+▁manjakaray	-59642
+▁mankiewicz	-59643
+▁margherita	-59644
+▁mariôlôjia	-59645
+▁maroseraña	-59646
+▁marseillan	-59647
+▁meteôrôida	-59648
+▁mifanahaka	-59649
+▁mikararana	-59650
+▁milanković	-59651
+▁miraharaha	-59652
+▁miredareda	-59653
+▁mirenireny	-59654
+▁misalasala	-59655
+▁mississipi	-59656
+▁mitapelaka	-59657
+▁mitsoriaka	-59658
+▁mouvements	-59659
+▁mozambique	-59660
+▁mpampahory	-59661
+▁mpanankato	-59662
+▁mpianakavy	-59663
+▁mpisintaka	-59664
+▁mpitsikilo	-59665
+▁namboariny	-59666
+▁nampakatra	-59667
+▁nampanambo	-59668
+▁nanafihany	-59669
+▁nanambaran	-59670
+▁nanapahany	-59671
+▁nanatsoaka	-59672
+▁nandefasan	-59673
+▁nandefitra	-59674
+▁nandritran	-59675
+▁nandrosoan	-59676
+▁natsahatra	-59677
+▁natzweiler	-59678
+▁navigateur	-59679
+▁nazianzôsy	-59680
+▁neognathae	-59681
+▁niankohoka	-59682
+▁niantsoina	-59683
+▁nifindrany	-59684
+▁niheverana	-59685
+▁nikôtinina	-59686
+▁nisalasala	-59687
+▁nitenenana	-59688
+▁nitoriteny	-59689
+▁niverenany	-59690
+▁nofaritany	-59691
+▁nofehezina	-59692
+▁nofinofiny	-59693
+▁nohafarana	-59694
+▁noresahina	-59695
+▁northfield	-59696
+▁nosokirina	-59697
+▁notantanin	-59698
+▁notapahiny	-59699
+▁notaterina	-59700
+▁notoheriny	-59701
+▁notohizany	-59702
+▁notsinjara	-59703
+▁notsipahin	-59704
+▁oberhoffen	-59705
+▁officinale	-59706
+▁oranjestad	-59707
+▁otrikanina	-59708
+▁paleôzôika	-59709
+▁paramecium	-59710
+▁peninsular	-59711
+▁pennisetum	-59712
+▁petrôsimia	-59713
+▁peyrefitte	-59714
+▁philosophy	-59715
+▁pierremont	-59716
+▁pleasanton	-59717
+▁portiogaly	-59718
+▁procumbens	-59719
+▁propagandy	-59720
+▁proteinina	-59721
+▁ptolemaios	-59722
+▁ptolemeosy	-59723
+▁publishers	-59724
+▁rakotoarin	-59725
+▁ramaintsoa	-59726
+▁ramakararo	-59727
+▁ranaivoson	-59728
+▁randriaman	-59729
+▁razanamasy	-59730
+▁remoncourt	-59731
+▁renneville	-59732
+▁rhodolepis	-59733
+▁références	-59734
+▁résistance	-59735
+▁santacroce	-59736
+▁sariitatra	-59737
+▁scriptures	-59738
+▁secondaire	-59739
+▁serbianina	-59740
+▁sesôstrisy	-59741
+▁shenandoah	-59742
+▁shevchenko	-59743
+▁shinnecock	-59744
+▁silimanita	-59745
+▁silvestris	-59746
+▁smartphone	-59747
+▁soratanana	-59748
+▁sousceyrac	-59749
+▁suaveolens	-59750
+▁subtropika	-59751
+▁sylvestris	-59752
+▁tampoketsa	-59753
+▁tanalensis	-59754
+▁tarentaise	-59755
+▁tirseniana	-59756
+▁toejavatra	-59757
+▁tolongoina	-59758
+▁tondrahana	-59759
+▁torimasony	-59760
+▁torricelli	-59761
+▁torstenson	-59762
+▁tourrettes	-59763
+▁traikefany	-59764
+▁tranokalan	-59765
+▁tratrarina	-59766
+▁triaucourt	-59767
+▁trôpikalin	-59768
+▁tymoshenko	-59769
+▁ungersberg	-59770
+▁unionville	-59771
+▁vacheresse	-59772
+▁valparaíso	-59773
+▁vaubecourt	-59774
+▁vauchelles	-59775
+▁velarantan	-59776
+▁vendeville	-59777
+▁vereenigde	-59778
+▁voatendrin	-59779
+▁volleyball	-59780
+▁vorarlberg	-59781
+▁waterville	-59782
+▁waynesboro	-59783
+▁westermann	-59784
+▁wikicities	-59785
+▁zanamalata	-59786
+▁zanapelana	-59787
+▁zôrôbabela	-59788
+▁ôrdônansin	-59789
+analanjirofo	-59790
+doriamanjaka	-59791
+dranomasimbe	-59792
+dratsimivily	-59793
+driananahary	-59794
+elaeodendron	-59795
+gouvernement	-59796
+hippopotamus	-59797
+intsiatosika	-59798
+lambovitaony	-59799
+missionnaire	-59800
+mitsambikina	-59801
+prôtektôrata	-59802
+thouberville	-59803
+wolfenbüttel	-59804
+▁albuquerque	-59805
+▁alençonnais	-59806
+▁alimanakara	-59807
+▁ambatomanga	-59808
+▁ampianariny	-59809
+▁ampiarahana	-59810
+▁ampielezana	-59811
+▁amygdalinum	-59812
+▁andrainjato	-59813
+▁andranomamy	-59814
+▁anjakazakan	-59815
+▁antetsimeto	-59816
+▁apollinaire	-59817
+▁appalachian	-59818
+▁arborescens	-59819
+▁archipelago	-59820
+▁artifisialy	-59821
+▁baldassarre	-59822
+▁balochistan	-59823
+▁beauharnais	-59824
+▁bentivoglio	-59825
+▁blanquefort	-59826
+▁bolgarianan	-59827
+▁bourdonnaye	-59828
+▁brichanteau	-59829
+▁cantacuzène	-59830
+▁caprimulgus	-59831
+▁caryophylla	-59832
+▁cedrelopsis	-59833
+▁chamalières	-59834
+▁chavengeois	-59835
+▁chlorophyta	-59836
+▁christoffel	-59837
+▁clérambault	-59838
+▁comparative	-59839
+▁decazeville	-59840
+▁deoterônômy	-59841
+▁depauperata	-59842
+▁discography	-59843
+▁dobrovolski	-59844
+▁dostoyevsky	-59845
+▁dourdannais	-59846
+▁drakensberg	-59847
+▁electronics	-59848
+▁engineering	-59849
+▁equisetidae	-59850
+▁eritreritry	-59851
+▁facchinetti	-59852
+▁fahanterana	-59853
+▁fahasimbany	-59854
+▁fahatairana	-59855
+▁fahatakaran	-59856
+▁fahavakisan	-59857
+▁fanahotoana	-59858
+▁fanamasinam	-59859
+▁fandehanany	-59860
+▁fandevonana	-59861
+▁fandihizana	-59862
+▁fandinihany	-59863
+▁fandrafetan	-59864
+▁fandrariana	-59865
+▁fanjavonana	-59866
+▁fantantsika	-59867
+▁fiandaniana	-59868
+▁fiangaliana	-59869
+▁fihamafisan	-59870
+▁fikarakaran	-59871
+▁fikorianany	-59872
+▁firotsahany	-59873
+▁fitampodian	-59874
+▁fitanjahany	-59875
+▁fitantarany	-59876
+▁fitombenana	-59877
+▁fizakantena	-59878
+▁fombafomban	-59879
+▁gagnepainia	-59880
+▁galliformes	-59881
+▁glaucescens	-59882
+▁grandifolia	-59883
+▁guerassimov	-59884
+▁gymnophiona	-59885
+▁hampiharina	-59886
+▁hampitovina	-59887
+▁hanangonana	-59888
+▁hanatrarana	-59889
+▁handaminana	-59890
+▁handringana	-59891
+▁handroahana	-59892
+▁herinandron	-59893
+▁hipetrahana	-59894
+▁hippotragus	-59895
+▁hitadiavana	-59896
+▁hitrandraka	-59897
+▁hymenoptera	-59898
+▁ianteherana	-59899
+▁ilangilangy	-59900
+▁iroboroboan	-59901
+▁jaguariaíva	-59902
+▁kabalistika	-59903
+▁kalashnikov	-59904
+▁karakalpaka	-59905
+▁khorramabad	-59906
+▁kirkpatrick	-59907
+▁klavesinina	-59908
+▁klingenberg	-59909
+▁kôrdôfônina	-59910
+▁lahinaratra	-59911
+▁lalindalina	-59912
+▁latispinosa	-59913
+▁leucophylla	-59914
+▁lichtenberg	-59915
+▁loganiaceae	-59916
+▁malicornais	-59917
+▁mampihomehy	-59918
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+▁maromokotra	-59921
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+▁mifanandrif	-59927
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+▁montboucher	-59930
+▁montgomerie	-59931
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+▁pitheciidae	-59959
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+▁randriamamp	-59967
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+▁voazarazara	-59997
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+▁xiphophylla	-59999
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diff --git a/models/tokenizer/mg_tokenizer_8k.model b/models/tokenizer/mg_tokenizer_8k.model
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