Remove tokenizer example from method section
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<section id="method">
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<h2>How TurCOMET works</h2>
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<p class="lede">Turkish is agglutinative:
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<figure class="card figure" style="margin:0">
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<div class="img"><img src="img/architecture.webp" alt="TurCOMET architecture: frozen xCOMET-XL backbone with a trainable bottleneck that fuses five Turkish lexical features into the pooled representation" loading="lazy" width="1939" height="1053"></div>
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<figcaption><b>Figure 1.</b> The frozen xCOMET-XL backbone (3.5B parameters) is kept intact. The only addition is a violet bottleneck that fuses a five-dimensional Turkish feature vector into the pooled embedding: <i>h′ = h + W₂ tanh(W₁[h; f] + b₁) + b₂</i>, width 64.</figcaption>
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<section id="method">
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<h2>How TurCOMET works</h2>
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<p class="lede">Turkish is agglutinative: a single root can carry a long chain of derivational and inflectional suffixes, which the XLM-R sub-word tokenizer fragments aggressively. This over-segmentation depresses surface overlap and dilutes the pooled sentence representation, so TurCOMET feeds the metric explicit Turkish-aware signals.</p>
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<figure class="card figure" style="margin:0">
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<div class="img"><img src="img/architecture.webp" alt="TurCOMET architecture: frozen xCOMET-XL backbone with a trainable bottleneck that fuses five Turkish lexical features into the pooled representation" loading="lazy" width="1939" height="1053"></div>
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<figcaption><b>Figure 1.</b> The frozen xCOMET-XL backbone (3.5B parameters) is kept intact. The only addition is a violet bottleneck that fuses a five-dimensional Turkish feature vector into the pooled embedding: <i>h′ = h + W₂ tanh(W₁[h; f] + b₁) + b₂</i>, width 64.</figcaption>
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