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+*.pt filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
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+---
+title: ACSA Clothing Sentiment
+emoji: "👕"
+colorFrom: blue
+colorTo: indigo
+sdk: gradio
+sdk_version: 5.49.1
+python_version: "3.10"
+app_file: app.py
+pinned: false
+---
+
+# Aspect-Level Sentiment Analysis for Clothing Reviews
+
+Dual-interface consumer and merchant demo plus research dashboard for a BERT metadata-fusion ACSA model trained on 100,000 clothing reviews.
+
+## Included inference artifacts
+
+- Proposed metadata-fusion checkpoint and tokenizer
+- Matching `meta_encoder.pkl`
+- Overall, aspect-level, and ablation evaluation reports
diff --git a/__pycache__/app.cpython-314.pyc b/__pycache__/app.cpython-314.pyc
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+"""Dual-interface Hugging Face Space for clothing aspect-level sentiment analysis."""
+from __future__ import annotations
+
+import html
+import json
+import re
+import traceback
+from functools import lru_cache
+from pathlib import Path
+from typing import Any, Dict, List, Tuple
+
+try:
+ import huggingface_hub as _hf_hub
+ if not hasattr(_hf_hub, "HfFolder"):
+ class _HfFolderCompat:
+ @staticmethod
+ def get_token():
+ try:
+ return _hf_hub.get_token()
+ except Exception:
+ return None
+ @staticmethod
+ def save_token(token):
+ return None
+ @staticmethod
+ def delete_token():
+ return None
+ _hf_hub.HfFolder = _HfFolderCompat
+except Exception:
+ pass
+
+import gradio as gr
+
+from src import config as cfg
+from src.inference import AspectPredictor
+
+ROOT = Path(__file__).resolve().parent
+REPORT_DIR = ROOT / "reports"
+CHECKPOINT_DIR = ROOT / "checkpoints" / "meta_acsa"
+CHECKPOINT_PATH = CHECKPOINT_DIR / "best.pt"
+META_ENCODER_PATH = ROOT / "data" / "meta_encoder.pkl"
+ASPECTS = list(getattr(cfg, "ASPECTS", ["SIZE", "MATERIAL", "QUALITY", "APPEARANCE", "STYLE", "VALUE"]))
+
+ASPECT_DESCRIPTIONS = {
+ "SIZE": "Fit, length, sizing accuracy, runs large or small.",
+ "MATERIAL": "Fabric feel, thickness, breathability, and comfort.",
+ "QUALITY": "Workmanship, durability, seams, and washing performance.",
+ "APPEARANCE": "Color, print, pattern, image consistency, and visual look.",
+ "STYLE": "Cut, silhouette, fashionability, and styling appeal.",
+ "VALUE": "Price fairness, worthiness, return, and repurchase intent.",
+}
+ASPECT_KEYWORDS = {
+ "SIZE": ["size", "fit", "fits", "small", "large", "tight", "loose", "xl", "medium", "waist", "length", "runs"],
+ "MATERIAL": ["material", "fabric", "cotton", "polyester", "soft", "scratchy", "thin", "thick", "stretch", "breathable"],
+ "QUALITY": ["quality", "stitch", "stitching", "seam", "wash", "durable", "cheap", "ripped", "tear", "button", "zipper"],
+ "APPEARANCE": ["look", "looks", "color", "photo", "picture", "print", "design", "pattern", "beautiful", "cute"],
+ "STYLE": ["style", "stylish", "flattering", "casual", "formal", "silhouette", "cut", "shape", "cropped"],
+ "VALUE": ["price", "worth", "value", "money", "expensive", "cheap", "return", "buy", "recommend"],
+}
+LABEL_BG = {"Positive": "#dcfce7", "Negative": "#fee2e2", "Not_Mentioned": "#f1f5f9", "Neutral": "#e0f2fe"}
+LABEL_FG = {"Positive": "#15803d", "Negative": "#b91c1c", "Not_Mentioned": "#475569", "Neutral": "#0369a1"}
+
+PRODUCTS = [
+ {"name": "Cotton Graphic Tee", "category": "Tops", "features": "100% Cotton, Slim Fit, Machine Wash Cold, Graphic Print", "categories": "Clothing > Men > T-Shirts > Graphic Tees", "price": 19.99, "average_rating": 4.2, "rating_number": 312, "tags": ["cotton", "casual", "print"], "review": "The size runs really small, I ordered an XL but it fits like a Medium. The fabric feels soft and the print looks great."},
+ {"name": "Stretch Yoga Leggings", "category": "Bottoms", "features": "Nylon Spandex Blend, High Waist, Four-Way Stretch, Moisture Wicking", "categories": "Clothing > Women > Activewear > Leggings", "price": 29.99, "average_rating": 4.5, "rating_number": 1280, "tags": ["stretch", "activewear", "high waist"], "review": "These leggings fit perfectly and the stretch is comfortable. The material is not see-through, but the seams started to loosen after washing."},
+ {"name": "Oversized Denim Jacket", "category": "Outerwear", "features": "Denim Cotton Blend, Oversized Fit, Button Front, Distressed Wash", "categories": "Clothing > Women > Jackets > Denim Jackets", "price": 58.00, "average_rating": 4.0, "rating_number": 447, "tags": ["denim", "oversized", "jacket"], "review": "The oversized style is cute and the color looks like the photo. It is heavier than expected and the buttons feel a little cheap."},
+ {"name": "Floral Summer Dress", "category": "Dresses", "features": "Rayon Blend, Floral Print, A-Line, Lightweight, V-Neck", "categories": "Clothing > Women > Dresses > Summer Dresses", "price": 36.50, "average_rating": 4.3, "rating_number": 864, "tags": ["floral", "summer", "dress"], "review": "The dress looks beautiful and the floral print is exactly as shown. The waist is a bit tight and the fabric wrinkles easily."},
+ {"name": "Fleece Pullover Hoodie", "category": "Tops", "features": "Cotton Polyester Fleece, Regular Fit, Kangaroo Pocket, Ribbed Cuffs", "categories": "Clothing > Unisex > Hoodies > Pullover Hoodies", "price": 42.99, "average_rating": 4.6, "rating_number": 2214, "tags": ["fleece", "hoodie", "warm"], "review": "Very warm and soft hoodie. The quality feels good for the price, though the sleeves are a little long for me."},
+ {"name": "Linen Button-Up Shirt", "category": "Tops", "features": "Linen Cotton Blend, Relaxed Fit, Button Front, Breathable Fabric", "categories": "Clothing > Men > Shirts > Button-Up Shirts", "price": 34.99, "average_rating": 3.9, "rating_number": 186, "tags": ["linen", "breathable", "shirt"], "review": "The shirt is breathable and stylish, but it wrinkles badly and the stitching near one button came loose."},
+]
+
+
+def _safe_float(value: Any, default: float = 0.0) -> float:
+ try:
+ if value in (None, ""):
+ return default
+ return float(value)
+ except Exception:
+ return default
+
+
+def _esc(value: Any) -> str:
+ return html.escape(str(value))
+
+
+def _pct(value: Any) -> str:
+ try:
+ return f"{float(value) * 100:.2f}%"
+ except Exception:
+ return "-"
+
+
+def _num(value: Any) -> str:
+ try:
+ return f"{float(value):.4f}"
+ except Exception:
+ return "-"
+
+
+def _load_json(name: str) -> Dict[str, Any]:
+ path = REPORT_DIR / name
+ try:
+ return json.loads(path.read_text(encoding="utf-8")) if path.exists() else {}
+ except Exception:
+ return {}
+
+
+@lru_cache(maxsize=1)
+def _predictor() -> AspectPredictor:
+ return AspectPredictor(checkpoint_dir=CHECKPOINT_DIR)
+
+
+def _product_names() -> List[str]:
+ return [p["name"] for p in PRODUCTS]
+
+
+def _get_product(name: str) -> Dict[str, Any]:
+ return next((p for p in PRODUCTS if p["name"] == name), PRODUCTS[0])
+
+
+def _meta(product_or_meta: Dict[str, Any]) -> Dict[str, Any]:
+ return {
+ "features_text": product_or_meta.get("features", product_or_meta.get("features_text", "")),
+ "categories_text": product_or_meta.get("categories", product_or_meta.get("categories_text", "")),
+ "price": _safe_float(product_or_meta.get("price")),
+ "average_rating": _safe_float(product_or_meta.get("average_rating")),
+ "rating_number": _safe_float(product_or_meta.get("rating_number")),
+ }
+
+
+@lru_cache(maxsize=64)
+def _predict_product(product_name: str) -> Dict[str, Any]:
+ product = _get_product(product_name)
+ return _predictor().predict(product["review"], _meta(product))
+
+
+def _predict_custom(review: str, features: str, categories: str, price: Any, rating: Any, count: Any) -> Dict[str, Any]:
+ meta = {"features_text": features or "", "categories_text": categories or "", "price": _safe_float(price), "average_rating": _safe_float(rating), "rating_number": _safe_float(count)}
+ return _predictor().predict(review or "No review text provided.", meta)
+
+
+def _error_html(detail: str) -> str:
+ return f'Prediction could not run.Technical detail
{_esc(detail)} '
+
+
+def _chip(label: str) -> str:
+ bg = LABEL_BG.get(label, "#f1f5f9")
+ fg = LABEL_FG.get(label, "#334155")
+ return f'{_esc(label)}'
+
+
+def _keyword_hits(text: str, aspect: str) -> List[str]:
+ low = (text or "").lower()
+ hits = [kw for kw in ASPECT_KEYWORDS.get(aspect, []) if kw.lower() in low]
+ return list(dict.fromkeys(hits))[:8]
+
+
+def _highlight_review(text: str, aspect: str) -> str:
+ safe = _esc(text)
+ keys: List[str] = []
+ if aspect != "All":
+ keys = ASPECT_KEYWORDS.get(aspect, [])
+ else:
+ for items in ASPECT_KEYWORDS.values():
+ keys.extend(items)
+ for kw in sorted(set(keys), key=len, reverse=True):
+ safe = re.sub(rf"\b({re.escape(kw)})\b", r"\1", safe, flags=re.IGNORECASE)
+ return f'{safe}
'
+
+
+def _overall_html(result: Dict[str, Any]) -> str:
+ overall = result.get("overall", {})
+ label = overall.get("label", "Unknown")
+ conf = _safe_float(overall.get("confidence"))
+ probs = overall.get("class_probs", {})
+ bars = []
+ for name in ["Negative", "Neutral", "Positive"]:
+ val = _safe_float(probs.get(name))
+ bars.append(f'')
+ return f'Overall sentiment
{_chip(label)} confidence {conf:.2f}
{"".join(bars)}
Top metadata source: {_esc(src.get("source", "-"))} ({_safe_float(src.get("weight")):.2f})
' if src else ""
+ cls = "focus" if selected_aspect in ("All", aspect) else "dim"
+ cards.append(f'{aspect}conf {conf:.2f}
{_chip(label)}
{_esc(ASPECT_DESCRIPTIONS.get(aspect, ""))}
{evidence}
{src_line}
' + "".join(cards) + '
'
+
+
+def _aspect_rows(result: Dict[str, Any], review: str) -> List[List[Any]]:
+ rows = []
+ for aspect in ASPECTS:
+ d = result.get("aspect_details", {}).get(aspect, {})
+ label = d.get("label", result.get("aspects", {}).get(aspect, "Unknown"))
+ rows.append([aspect, label, round(_safe_float(d.get("confidence")), 4), ", ".join(_keyword_hits(review, aspect)) or "No explicit keyword evidence"])
+ return rows
+
+
+def consumer_product_view(product_name: str, selected_aspect: str) -> Tuple[str, str, str, List[List[Any]]]:
+ product = _get_product(product_name)
+ try:
+ result = _predict_product(product_name)
+ except Exception:
+ return _error_html(traceback.format_exc(limit=5)), "", "", []
+ detail = f'{_esc(product["name"])}
{_esc(product["categories"])}
Price: ${_safe_float(product["price"]):.2f}Rating: {_safe_float(product["average_rating"]):.1f}Reviews: {int(_safe_float(product["rating_number"]))}
Metadata: {_esc(product["features"])}
{_overall_html(result)}
Key review evidence
{_highlight_review(product["review"], selected_aspect)}'
+ return detail, _aspect_cards(result, product["review"], selected_aspect), evidence, _aspect_rows(result, product["review"])
+
+
+def filter_products(aspect: str, sentiment: str, category: str, tags: List[str], min_rating: float) -> Tuple[List[List[Any]], str]:
+ rows = []
+ best = None
+ for product in PRODUCTS:
+ if category != "All" and product["category"] != category:
+ continue
+ if tags and not set(tags).issubset(set(product.get("tags", []))):
+ continue
+ if _safe_float(product["average_rating"]) < _safe_float(min_rating):
+ continue
+ try:
+ result = _predict_product(product["name"])
+ except Exception:
+ continue
+ if aspect == "Overall":
+ d = result.get("overall", {})
+ else:
+ d = result.get("aspect_details", {}).get(aspect, {})
+ label = d.get("label", "Unknown")
+ conf = _safe_float(d.get("confidence"))
+ if sentiment != "Any" and label != sentiment:
+ continue
+ rows.append([product["name"], product["category"], label, round(conf, 4), product["average_rating"], product["price"], product["features"]])
+ score = conf + 0.03 * _safe_float(product["average_rating"])
+ if best is None or score > best[0]:
+ best = (score, product["name"], label, conf)
+ summary = 'No product matched the current filters.
'
+ if best:
+ summary = f'Best match: {_esc(best[1])} - {_esc(aspect)} is {_esc(best[2])} with confidence {best[3]:.2f}.
'
+ return rows, summary
+
+
+def _payload() -> Dict[str, Dict[str, Any]]:
+ return {"eval": _load_json("evaluation_comparison.json"), "proposed": _load_json("per_aspect_proposed.json"), "no_meta": _load_json("per_aspect_acsa_no_meta.json"), "ablation": _load_json("ablation_summary.json")}
+
+
+def model_info_html() -> str:
+ data = _payload()
+ proposed = data["proposed"].get("overall", {})
+ ckpt_mb = CHECKPOINT_PATH.stat().st_size / (1024 * 1024) if CHECKPOINT_PATH.exists() else 0
+ rows = [("Training data", "Amazon 2023 Clothing, 100K review sample"), ("Backbone", getattr(cfg, "BERT_MODEL_NAME", "bert-base-uncased")), ("Core method", "Aspect-specific cross-attention metadata fusion"), ("Metadata", "features, categories, price, average rating, rating count"), ("Aspects", ", ".join(ASPECTS)), ("Best checkpoint", f"{ckpt_mb:.1f} MB"), ("Mean aspect F1", _pct(proposed.get("mean_macro_f1"))), ("Mean aspect accuracy", _pct(proposed.get("mean_accuracy")))]
+ body = "".join(f"| {_esc(k)} | {_esc(v)} |
" for k, v in rows)
+ return f''
+
+
+def research_cards_html() -> str:
+ data = _payload()
+ cmp = data["eval"].get("overall_3class_comparison", {})
+ proposed_aspect = data["proposed"].get("overall", {})
+ no_meta_aspect = data["no_meta"].get("overall", {})
+ proposed_overall = cmp.get("Proposed_BERT_Meta_Fusion__overall_head", {})
+ gain = _safe_float(proposed_aspect.get("mean_macro_f1")) - _safe_float(no_meta_aspect.get("mean_macro_f1"))
+ return f'Proposed Overall Accuracy{_pct(proposed_overall.get("accuracy"))}overall head
Proposed Aspect Accuracy{_pct(proposed_aspect.get("mean_accuracy"))}six-aspect mean
Metadata F1 Gain+{gain:.4f}vs no-metadata BERT ACSA
New product risk focus: {_esc(summary)}
This is a metadata screening tool, not a replacement for real review evaluation.
', rows
+
+
+def external_review_predict(review: str, features: str, categories: str, price: Any, rating: Any, count: Any, selected_aspect: str) -> Tuple[str, str, List[List[Any]]]:
+ try:
+ result = _predict_custom(review, features, categories, price, rating, count)
+ except Exception:
+ return _error_html(traceback.format_exc(limit=5)), "", []
+ return _overall_html(result), _aspect_cards(result, review or "", selected_aspect), _aspect_rows(result, review or "")
+
+
+def _status_html() -> str:
+ missing = []
+ if not CHECKPOINT_PATH.exists() or CHECKPOINT_PATH.stat().st_size < 1024 * 1024:
+ missing.append("checkpoints/meta_acsa/best.pt")
+ if not META_ENCODER_PATH.exists() or META_ENCODER_PATH.stat().st_size < 1024:
+ missing.append("data/meta_encoder.pkl")
+ if missing:
+ return 'Model artifacts missing: ' + _esc(", ".join(missing)) + '
'
+ return 'Model ready. 10W0715 checkpoint and metadata encoder are available.
'
+
+
+CSS = """
+:root { --accent:#f97316; --ink:#0f172a; --muted:#475569; --line:#dbe3ef; }
+.gradio-container { max-width:1240px !important; margin:auto !important; color:var(--ink); }
+#hero { border:1px solid var(--line); background:#f8fbff; border-radius:8px; padding:22px 28px; margin:10px 0 22px; }
+#hero h1 { margin:0 0 8px; font-size:30px; line-height:1.15; }
+#hero p { margin:0; color:#334155; }
+button.primary, .gradio-button.primary { background:var(--accent) !important; border-color:var(--accent) !important; color:white !important; font-weight:700 !important; }
+.status { border-radius:8px; padding:12px 14px; margin:8px 0 18px; border:1px solid var(--line); }
+.status.ok { background:#ecfdf5; border-color:#86efac; color:#065f46; }
+.status.bad { background:#fff1f2; border-color:#fda4af; color:#991b1b; }
+.product-card, .overall-card, .note-card { border:1px solid var(--line); border-radius:8px; padding:16px; background:white; }
+.muted { color:var(--muted); }
+.meta-pills { display:flex; flex-wrap:wrap; gap:8px; margin:10px 0; }
+.meta-pills span { background:#f1f5f9; border:1px solid #e2e8f0; border-radius:999px; padding:5px 9px; font-size:13px; }
+.chip { display:inline-block; border-radius:999px; padding:5px 10px; font-weight:700; font-size:13px; }
+.conf { color:#334155; font-size:13px; margin-left:8px; }
+.small-label { color:#475569; font-size:13px; margin-bottom:8px; }
+.prob-row { display:grid; grid-template-columns:82px 1fr 44px; gap:8px; align-items:center; font-size:13px; margin:6px 0; }
+.bar { height:8px; background:#e2e8f0; border-radius:999px; overflow:hidden; }
+.bar i { display:block; height:100%; background:var(--accent); }
+.aspect-grid { display:grid; grid-template-columns:repeat(3, minmax(0, 1fr)); gap:12px; }
+.aspect-card { border:1px solid var(--line); border-top:4px solid #64748b; border-radius:8px; padding:13px; background:white; min-height:165px; }
+.aspect-card.focus { border-top-color:var(--accent); box-shadow:0 2px 10px rgba(15,23,42,.08); }
+.aspect-card.dim { opacity:.66; }
+.aspect-head { display:flex; justify-content:space-between; align-items:center; margin-bottom:8px; }
+.aspect-head span, .source-line { color:#475569; font-size:12px; }
+.aspect-card p { margin:8px 0; color:#334155; font-size:13px; }
+.evidence-row { display:flex; flex-wrap:wrap; gap:5px; margin-top:8px; }
+.evidence-token { color:#1d4ed8; background:#eef2ff; border:1px solid #bfdbfe; border-radius:999px; padding:3px 8px; font-size:12px; }
+.review-box { border:1px dashed #cbd5e1; background:#f8fafc; border-radius:8px; padding:14px; line-height:1.6; }
+mark { background:#fde68a; color:#111827; border-radius:4px; padding:1px 3px; }
+.metric-grid { display:grid; grid-template-columns:repeat(3, 1fr); gap:14px; margin:8px 0 18px; }
+.metric { border:1px solid var(--line); border-radius:8px; padding:16px; background:white; }
+.metric span { display:block; color:#334155; font-size:13px; }
+.metric b { display:block; font-size:28px; margin:6px 0; }
+.metric small { color:#475569; }
+.table-wrap { border:1px solid var(--line); border-radius:8px; overflow:hidden; background:white; }
+.kv-table { width:100%; border-collapse:collapse; }
+.kv-table td { border-bottom:1px solid #e2e8f0; padding:9px 12px; }
+.kv-table td:first-child { width:220px; color:#334155; font-weight:700; background:#f8fafc; }
+@media (max-width:860px) { .aspect-grid, .metric-grid { grid-template-columns:1fr; } }
+"""
+
+
+def build_app() -> gr.Blocks:
+ categories = ["All"] + sorted({p["category"] for p in PRODUCTS})
+ tags = sorted({tag for p in PRODUCTS for tag in p.get("tags", [])})
+ with gr.Blocks(css=CSS, title="Clothing Sentiment Analysis") as demo:
+ gr.HTML('Aspect-Level Sentiment Analysis for Clothing Reviews
BERT + metadata cross-attention fusion for consumer decision support and merchant diagnostics.
Aspect-Level Sentiment with Metadata Fusion: Explanations
+Highlights show the strongest text evidence for each aspect. green = Positive, red = Negative, grey = Not_Mentioned. Metadata rows show which source the model attends to for each aspect.
+Example 1
+
Rating: 1 | Category: Strands
+
Bad quality control I ordered despite all the bad reviews. Well that didn’t work as it was just pack in a baggie as like most of the reviews state. Then the blue and white flowers with charms were all attached backwards. I am in the process of returning it. I will not be asking for an exchange as I do not wish to keep returning this item until I get a good one. So very sad as this could have been a beautiful necklace. Plus with as expensive as this is you would think it would have better packaging. I have bought for much cheaper with nice packaging. Unfortunately I will not be buying any more of this brand as it had put a bad taste in my mouth. Do better!
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Negative
+
Top text evidence: badgoodbeautifulnice
+
bad quality control i ordered despite all the bad reviews . well that didn ’ t work as it was just pack in a baggie as like most of the reviews state . then the blue and white flowers with charms were all attached backwards . i am in the process of returning it . i will not be asking for an exchange as i do not wish to keep returning this item until i get a good one . so very sad as this could have been a beautiful necklace . plus with as expensive as this is you would think it would have better packaging . i have bought for much cheaper with nice packaging . unfortunately i will not be buying any more of this brand as it had put a bad taste in my mouth . do better !
+
Top metadata source: features 0.500 quality: strong
+
Explanation: SIZE is predicted as Negative. The main text evidence is "bad", "good", "beautiful", "nice", and the strongest metadata source is "features" (0.500).
+
+
+
MATERIAL: Negative
+
Top text evidence: badgoodbeautifulnice
+
bad quality control i ordered despite all the bad reviews . well that didn ’ t work as it was just pack in a baggie as like most of the reviews state . then the blue and white flowers with charms were all attached backwards . i am in the process of returning it . i will not be asking for an exchange as i do not wish to keep returning this item until i get a good one . so very sad as this could have been a beautiful necklace . plus with as expensive as this is you would think it would have better packaging . i have bought for much cheaper with nice packaging . unfortunately i will not be buying any more of this brand as it had put a bad taste in my mouth . do better !
+
Top metadata source: features 0.500 quality: strong
+
Explanation: MATERIAL is predicted as Negative. The main text evidence is "bad", "good", "beautiful", "nice", and the strongest metadata source is "features" (0.500).
+
+
+
QUALITY: Negative
+
Top text evidence: qualitybadgoodbeautifulnice
+
bad quality control i ordered despite all the bad reviews . well that didn ’ t work as it was just pack in a baggie as like most of the reviews state . then the blue and white flowers with charms were all attached backwards . i am in the process of returning it . i will not be asking for an exchange as i do not wish to keep returning this item until i get a good one . so very sad as this could have been a beautiful necklace . plus with as expensive as this is you would think it would have better packaging . i have bought for much cheaper with nice packaging . unfortunately i will not be buying any more of this brand as it had put a bad taste in my mouth . do better !
+
Top metadata source: features 0.500 quality: strong
+
Explanation: QUALITY is predicted as Negative. The main text evidence is "quality", "bad", "good", "beautiful", and the strongest metadata source is "features" (0.500).
+
+
+
APPEARANCE: Positive
+
Top text evidence: beautifulbadgoodnice
+
bad quality control i ordered despite all the bad reviews . well that didn ’ t work as it was just pack in a baggie as like most of the reviews state . then the blue and white flowers with charms were all attached backwards . i am in the process of returning it . i will not be asking for an exchange as i do not wish to keep returning this item until i get a good one . so very sad as this could have been a beautiful necklace . plus with as expensive as this is you would think it would have better packaging . i have bought for much cheaper with nice packaging . unfortunately i will not be buying any more of this brand as it had put a bad taste in my mouth . do better !
+
Top metadata source: features 0.500 quality: strong
+
Explanation: APPEARANCE is predicted as Positive. The main text evidence is "beautiful", "bad", "good", "nice", and the strongest metadata source is "features" (0.500).
+
+
+
STYLE: Negative
+
Top text evidence: badgoodbeautifulnice
+
bad quality control i ordered despite all the bad reviews . well that didn ’ t work as it was just pack in a baggie as like most of the reviews state . then the blue and white flowers with charms were all attached backwards . i am in the process of returning it . i will not be asking for an exchange as i do not wish to keep returning this item until i get a good one . so very sad as this could have been a beautiful necklace . plus with as expensive as this is you would think it would have better packaging . i have bought for much cheaper with nice packaging . unfortunately i will not be buying any more of this brand as it had put a bad taste in my mouth . do better !
+
Top metadata source: features 0.500 quality: strong
+
Explanation: STYLE is predicted as Negative. The main text evidence is "bad", "good", "beautiful", "nice", and the strongest metadata source is "features" (0.500).
+
+
+
VALUE: Negative
+
Top text evidence: expensivebadgoodbeautifulnice
+
bad quality control i ordered despite all the bad reviews . well that didn ’ t work as it was just pack in a baggie as like most of the reviews state . then the blue and white flowers with charms were all attached backwards . i am in the process of returning it . i will not be asking for an exchange as i do not wish to keep returning this item until i get a good one . so very sad as this could have been a beautiful necklace . plus with as expensive as this is you would think it would have better packaging . i have bought for much cheaper with nice packaging . unfortunately i will not be buying any more of this brand as it had put a bad taste in my mouth . do better !
+
Top metadata source: features 0.500 quality: strong
+
Explanation: VALUE is predicted as Negative. The main text evidence is "expensive", "bad", "good", "beautiful", and the strongest metadata source is "features" (0.500).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.50
categories 0.25
numeric 0.25
MATERIAL
features 0.50
categories 0.25
numeric 0.25
QUALITY
features 0.50
categories 0.25
numeric 0.25
APPEARANCE
features 0.50
categories 0.25
numeric 0.25
STYLE
features 0.50
categories 0.25
numeric 0.25
VALUE
features 0.50
categories 0.25
numeric 0.25
+
Example 2
+
Rating: 1 | Category: Rash Guard Shirts
+
Very small for size and returned Too tight for size and Iborderwd extra large.
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Negative
+
Top text evidence: smalltightlargesizereturned
+
very small for size and returned too tight for size and iborderwd extra large .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: SIZE is predicted as Negative. The main text evidence is "small", "tight", "large", "size", and the strongest metadata source is "features" (0.500).
+
+
+
MATERIAL: Not_Mentioned
+
Top text evidence: smalltightreturnedlarge
+
very small for size and returned too tight for size and iborderwd extra large .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: MATERIAL is predicted as Not_Mentioned. The main text evidence is "small", "tight", "returned", "large", and the strongest metadata source is "features" (0.500).
+
+
+
QUALITY: Not_Mentioned
+
Top text evidence: smalltightreturnedlarge
+
very small for size and returned too tight for size and iborderwd extra large .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: QUALITY is predicted as Not_Mentioned. The main text evidence is "small", "tight", "returned", "large", and the strongest metadata source is "features" (0.500).
+
+
+
APPEARANCE: Not_Mentioned
+
Top text evidence: smalltightreturnedlarge
+
very small for size and returned too tight for size and iborderwd extra large .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: APPEARANCE is predicted as Not_Mentioned. The main text evidence is "small", "tight", "returned", "large", and the strongest metadata source is "features" (0.500).
+
+
+
STYLE: Not_Mentioned
+
Top text evidence: smalltightreturnedlarge
+
very small for size and returned too tight for size and iborderwd extra large .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: STYLE is predicted as Not_Mentioned. The main text evidence is "small", "tight", "returned", "large", and the strongest metadata source is "features" (0.500).
+
+
+
VALUE: Not_Mentioned
+
Top text evidence: smalltightreturnedlarge
+
very small for size and returned too tight for size and iborderwd extra large .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: VALUE is predicted as Not_Mentioned. The main text evidence is "small", "tight", "returned", "large", and the strongest metadata source is "features" (0.500).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.50
categories 0.25
numeric 0.25
MATERIAL
features 0.50
categories 0.25
numeric 0.25
QUALITY
features 0.50
categories 0.25
numeric 0.25
APPEARANCE
features 0.50
categories 0.25
numeric 0.25
STYLE
features 0.50
categories 0.25
numeric 0.25
VALUE
features 0.50
categories 0.25
numeric 0.25
+
Example 3
+
Rating: 2 | Category: Identification
+
Not great Not comfortable to wear. The information portion of the bracelet has very sharp edges. Adjusting the length requires a tool. You can't push down the locking part by hand. So broken clasp after long wait. They did issue a refund without requiring me to return the item
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Negative
+
Top text evidence: lengthgreatcomfortablereturn
+
not great not comfortable to wear . the information portion of the bracelet has very sharp edges . adjusting the length requires a tool . you can ' t push down the locking part by hand . so broken clasp after long wait . they did issue a refund without requiring me to return the item
+
Top metadata source: features 0.750 quality: strong
+
Explanation: SIZE is predicted as Negative. The main text evidence is "length", "great", "comfortable", "return", and the strongest metadata source is "features" (0.750).
+
+
+
MATERIAL: Not_Mentioned
+
Top text evidence: greatcomfortablereturn
+
not great not comfortable to wear . the information portion of the bracelet has very sharp edges . adjusting the length requires a tool . you can ' t push down the locking part by hand . so broken clasp after long wait . they did issue a refund without requiring me to return the item
+
Top metadata source: features 0.500 quality: strong
+
Explanation: MATERIAL is predicted as Not_Mentioned. The main text evidence is "great", "comfortable", "return", and the strongest metadata source is "features" (0.500).
+
+
+
QUALITY: Negative
+
Top text evidence: greatcomfortablereturn
+
not great not comfortable to wear . the information portion of the bracelet has very sharp edges . adjusting the length requires a tool . you can ' t push down the locking part by hand . so broken clasp after long wait . they did issue a refund without requiring me to return the item
+
Top metadata source: features 0.750 quality: strong
+
Explanation: QUALITY is predicted as Negative. The main text evidence is "great", "comfortable", "return", and the strongest metadata source is "features" (0.750).
+
+
+
APPEARANCE: Not_Mentioned
+
Top text evidence: greatcomfortablereturn
+
not great not comfortable to wear . the information portion of the bracelet has very sharp edges . adjusting the length requires a tool . you can ' t push down the locking part by hand . so broken clasp after long wait . they did issue a refund without requiring me to return the item
+
Top metadata source: features 0.750 quality: strong
+
Explanation: APPEARANCE is predicted as Not_Mentioned. The main text evidence is "great", "comfortable", "return", and the strongest metadata source is "features" (0.750).
+
+
+
STYLE: Not_Mentioned
+
Top text evidence: greatcomfortablereturn
+
not great not comfortable to wear . the information portion of the bracelet has very sharp edges . adjusting the length requires a tool . you can ' t push down the locking part by hand . so broken clasp after long wait . they did issue a refund without requiring me to return the item
+
Top metadata source: features 0.750 quality: strong
+
Explanation: STYLE is predicted as Not_Mentioned. The main text evidence is "great", "comfortable", "return", and the strongest metadata source is "features" (0.750).
+
+
+
VALUE: Negative
+
Top text evidence: greatcomfortablereturn
+
not great not comfortable to wear . the information portion of the bracelet has very sharp edges . adjusting the length requires a tool . you can ' t push down the locking part by hand . so broken clasp after long wait . they did issue a refund without requiring me to return the item
+
Top metadata source: features 0.500 quality: strong
+
Explanation: VALUE is predicted as Negative. The main text evidence is "great", "comfortable", "return", and the strongest metadata source is "features" (0.500).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.75
categories 0.25
numeric 0.00
MATERIAL
features 0.50
categories 0.25
numeric 0.25
QUALITY
features 0.75
categories 0.25
numeric 0.00
APPEARANCE
features 0.75
categories 0.25
numeric 0.00
STYLE
features 0.75
categories 0.25
numeric 0.00
VALUE
features 0.50
categories 0.25
numeric 0.25
+
Example 4
+
Rating: 2 | Category: Wallets
+
Two Stars loved it until the pin fell out after having it only a month
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Not_Mentioned
+
Top text evidence: loved
+
two stars loved it until the pin fell out after having it only a month
+
Top metadata source: features 0.750 quality: moderate
+
Explanation: SIZE is predicted as Not_Mentioned. The main text evidence is "loved", and the strongest metadata source is "features" (0.750).
+
+
+
MATERIAL: Not_Mentioned
+
Top text evidence: loved
+
two stars loved it until the pin fell out after having it only a month
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: MATERIAL is predicted as Not_Mentioned. The main text evidence is "loved", and the strongest metadata source is "features" (0.500).
+
+
+
QUALITY: Not_Mentioned
+
Top text evidence: loved
+
two stars loved it until the pin fell out after having it only a month
+
Top metadata source: features 0.750 quality: moderate
+
Explanation: QUALITY is predicted as Not_Mentioned. The main text evidence is "loved", and the strongest metadata source is "features" (0.750).
+
+
+
APPEARANCE: Not_Mentioned
+
Top text evidence: loved
+
two stars loved it until the pin fell out after having it only a month
+
Top metadata source: features 0.750 quality: moderate
+
Explanation: APPEARANCE is predicted as Not_Mentioned. The main text evidence is "loved", and the strongest metadata source is "features" (0.750).
+
+
+
STYLE: Not_Mentioned
+
Top text evidence: loved
+
two stars loved it until the pin fell out after having it only a month
+
Top metadata source: features 0.750 quality: moderate
+
Explanation: STYLE is predicted as Not_Mentioned. The main text evidence is "loved", and the strongest metadata source is "features" (0.750).
+
+
+
VALUE: Not_Mentioned
+
Top text evidence: loved
+
two stars loved it until the pin fell out after having it only a month
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: VALUE is predicted as Not_Mentioned. The main text evidence is "loved", and the strongest metadata source is "features" (0.500).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.75
categories 0.25
numeric 0.00
MATERIAL
features 0.50
categories 0.25
numeric 0.25
QUALITY
features 0.75
categories 0.25
numeric 0.00
APPEARANCE
features 0.75
categories 0.25
numeric 0.00
STYLE
features 0.75
categories 0.25
numeric 0.00
VALUE
features 0.50
categories 0.25
numeric 0.25
+
Example 5
+
Rating: 3 | Category: Cocktail
+
Okay Not the best quality, pretty skimpy
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Not_Mentioned
+
okay not the best quality , pretty skimpy
+
Top metadata source: features 0.500 quality: weak
+
Explanation: SIZE is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.500).
+
+
+
MATERIAL: Not_Mentioned
+
okay not the best quality , pretty skimpy
+
Top metadata source: features 0.500 quality: weak
+
Explanation: MATERIAL is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.500).
+
+
+
QUALITY: Not_Mentioned
+
Top text evidence: quality
+
okay not the best quality , pretty skimpy
+
Top metadata source: features 0.750 quality: moderate
+
Explanation: QUALITY is predicted as Not_Mentioned. The main text evidence is "quality", and the strongest metadata source is "features" (0.750).
+
+
+
APPEARANCE: Not_Mentioned
+
okay not the best quality , pretty skimpy
+
Top metadata source: features 0.750 quality: weak
+
Explanation: APPEARANCE is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.750).
+
+
+
STYLE: Not_Mentioned
+
okay not the best quality , pretty skimpy
+
Top metadata source: features 0.750 quality: weak
+
Explanation: STYLE is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.750).
+
+
+
VALUE: Not_Mentioned
+
okay not the best quality , pretty skimpy
+
Top metadata source: features 0.500 quality: weak
+
Explanation: VALUE is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.500).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.50
categories 0.25
numeric 0.25
MATERIAL
features 0.50
categories 0.25
numeric 0.25
QUALITY
features 0.75
categories 0.25
numeric 0.00
APPEARANCE
features 0.75
categories 0.25
numeric 0.00
STYLE
features 0.75
categories 0.25
numeric 0.00
VALUE
features 0.50
categories 0.25
numeric 0.25
+
Example 6
+
Rating: 3 | Category: Aprons
+
Okay don't have very much to say about this on ipad version, other than its okay
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Not_Mentioned
+
okay don ' t have very much to say about this on ipad version , other than its okay
+
Top metadata source: features 0.750 quality: weak
+
Explanation: SIZE is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.750).
+
+
+
MATERIAL: Not_Mentioned
+
okay don ' t have very much to say about this on ipad version , other than its okay
+
Top metadata source: features 0.750 quality: weak
+
Explanation: MATERIAL is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.750).
+
+
+
QUALITY: Not_Mentioned
+
okay don ' t have very much to say about this on ipad version , other than its okay
+
Top metadata source: features 0.750 quality: weak
+
Explanation: QUALITY is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.750).
+
+
+
APPEARANCE: Not_Mentioned
+
okay don ' t have very much to say about this on ipad version , other than its okay
+
Top metadata source: features 0.750 quality: weak
+
Explanation: APPEARANCE is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.750).
+
+
+
STYLE: Not_Mentioned
+
okay don ' t have very much to say about this on ipad version , other than its okay
+
Top metadata source: features 0.750 quality: weak
+
Explanation: STYLE is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.750).
+
+
+
VALUE: Not_Mentioned
+
okay don ' t have very much to say about this on ipad version , other than its okay
+
Top metadata source: features 0.749 quality: weak
+
Explanation: VALUE is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.749).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.75
categories 0.25
numeric 0.00
MATERIAL
features 0.75
categories 0.25
numeric 0.00
QUALITY
features 0.75
categories 0.25
numeric 0.00
APPEARANCE
features 0.75
categories 0.25
numeric 0.00
STYLE
features 0.75
categories 0.25
numeric 0.00
VALUE
features 0.75
categories 0.25
numeric 0.00
+
Example 7
+
Rating: 4 | Category: Shoe Horns & Boot Jacks
+
At the current price point, this is a decent shoe horn I was originally going to rate this 3 stars. However, for the current price of $7.99, I think this is a decent shoe horn. It is metal with a silicone covering on the upper part. It is also perfect for young children or adults who do not mind bending down to use a shoe horn. It is certainly better than plastic. This is packaged with a big cheap cinch-tie bag. I have no idea why this is included as probably 30 of these shoe horns could fit in that bag. This horn has the potential to bend because it is not super sturdy. I have a similar one with a wooden handle and that one is all bent just from use. My recommendation if you want a great shoe horn that is sturdier and can be used standing up, is to get this [[ASIN:B01M154SED 21" heavy duty one]] for the current price of $20.99 plus 5% off. I own one of these and had I purchased that one first, I would have never ordered any other. Do note, however, that it is very large and comes up to one's knees but it is fantastic. In summary, this one is decent and functional at the low price point but for something more sturdy and that will last longer, look into the other one I recommended.
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Negative
+
Top text evidence: largebigfitperfectcheapgreat
+
at the current price point , this is a decent shoe horn i was originally going to rate this 3 stars . however , for the current price of $ 7 . 99 , i think this is a decent shoe horn . it is metal with a silicone covering on the upper part . it is also perfect for young children or adults who do not mind bending down to use a shoe horn . it is certainly better than plastic . this is packaged with a big cheap cinch - tie bag . i have no idea why this is included as probably 30 of these shoe horns could fit in that bag . this horn has the potential to bend because it is not super sturdy . i have a similar one with a wooden handle and that one is all bent just from use . my recommendation if you want a great shoe horn that is sturdier and can be used standing up , is to get this [ [ asin : b01m154sed 21 " heavy duty one ] ] for the current price of $ 20 . 99 plus 5 % off . i own one of these and had i purchased that one first , i would have never ordered any other . do note , however , that it is very large and comes up to one ' s knees but it is fantastic . in summary
+
Top metadata source: features 0.500 quality: strong
+
Explanation: SIZE is predicted as Negative. The main text evidence is "large", "big", "fit", "perfect", and the strongest metadata source is "features" (0.500).
+
+
+
MATERIAL: Negative
+
Top text evidence: largeperfectcheapgreat
+
at the current price point , this is a decent shoe horn i was originally going to rate this 3 stars . however , for the current price of $ 7 . 99 , i think this is a decent shoe horn . it is metal with a silicone covering on the upper part . it is also perfect for young children or adults who do not mind bending down to use a shoe horn . it is certainly better than plastic . this is packaged with a big cheap cinch - tie bag . i have no idea why this is included as probably 30 of these shoe horns could fit in that bag . this horn has the potential to bend because it is not super sturdy . i have a similar one with a wooden handle and that one is all bent just from use . my recommendation if you want a great shoe horn that is sturdier and can be used standing up , is to get this [ [ asin : b01m154sed 21 " heavy duty one ] ] for the current price of $ 20 . 99 plus 5 % off . i own one of these and had i purchased that one first , i would have never ordered any other . do note , however , that it is very large and comes up to one ' s knees but it is fantastic . in summary
+
Top metadata source: features 0.500 quality: strong
+
Explanation: MATERIAL is predicted as Negative. The main text evidence is "large", "perfect", "cheap", "great", and the strongest metadata source is "features" (0.500).
+
+
+
QUALITY: Positive
+
Top text evidence: cheaplargeperfectgreat
+
at the current price point , this is a decent shoe horn i was originally going to rate this 3 stars . however , for the current price of $ 7 . 99 , i think this is a decent shoe horn . it is metal with a silicone covering on the upper part . it is also perfect for young children or adults who do not mind bending down to use a shoe horn . it is certainly better than plastic . this is packaged with a big cheap cinch - tie bag . i have no idea why this is included as probably 30 of these shoe horns could fit in that bag . this horn has the potential to bend because it is not super sturdy . i have a similar one with a wooden handle and that one is all bent just from use . my recommendation if you want a great shoe horn that is sturdier and can be used standing up , is to get this [ [ asin : b01m154sed 21 " heavy duty one ] ] for the current price of $ 20 . 99 plus 5 % off . i own one of these and had i purchased that one first , i would have never ordered any other . do note , however , that it is very large and comes up to one ' s knees but it is fantastic . in summary
+
Top metadata source: features 0.500 quality: strong
+
Explanation: QUALITY is predicted as Positive. The main text evidence is "cheap", "large", "perfect", "great", and the strongest metadata source is "features" (0.500).
+
+
+
APPEARANCE: Not_Mentioned
+
Top text evidence: largeperfectcheapgreat
+
at the current price point , this is a decent shoe horn i was originally going to rate this 3 stars . however , for the current price of $ 7 . 99 , i think this is a decent shoe horn . it is metal with a silicone covering on the upper part . it is also perfect for young children or adults who do not mind bending down to use a shoe horn . it is certainly better than plastic . this is packaged with a big cheap cinch - tie bag . i have no idea why this is included as probably 30 of these shoe horns could fit in that bag . this horn has the potential to bend because it is not super sturdy . i have a similar one with a wooden handle and that one is all bent just from use . my recommendation if you want a great shoe horn that is sturdier and can be used standing up , is to get this [ [ asin : b01m154sed 21 " heavy duty one ] ] for the current price of $ 20 . 99 plus 5 % off . i own one of these and had i purchased that one first , i would have never ordered any other . do note , however , that it is very large and comes up to one ' s knees but it is fantastic . in summary
+
Top metadata source: features 0.500 quality: strong
+
Explanation: APPEARANCE is predicted as Not_Mentioned. The main text evidence is "large", "perfect", "cheap", "great", and the strongest metadata source is "features" (0.500).
+
+
+
STYLE: Not_Mentioned
+
Top text evidence: largeperfectcheapgreat
+
at the current price point , this is a decent shoe horn i was originally going to rate this 3 stars . however , for the current price of $ 7 . 99 , i think this is a decent shoe horn . it is metal with a silicone covering on the upper part . it is also perfect for young children or adults who do not mind bending down to use a shoe horn . it is certainly better than plastic . this is packaged with a big cheap cinch - tie bag . i have no idea why this is included as probably 30 of these shoe horns could fit in that bag . this horn has the potential to bend because it is not super sturdy . i have a similar one with a wooden handle and that one is all bent just from use . my recommendation if you want a great shoe horn that is sturdier and can be used standing up , is to get this [ [ asin : b01m154sed 21 " heavy duty one ] ] for the current price of $ 20 . 99 plus 5 % off . i own one of these and had i purchased that one first , i would have never ordered any other . do note , however , that it is very large and comes up to one ' s knees but it is fantastic . in summary
+
Top metadata source: features 0.500 quality: strong
+
Explanation: STYLE is predicted as Not_Mentioned. The main text evidence is "large", "perfect", "cheap", "great", and the strongest metadata source is "features" (0.500).
+
+
+
VALUE: Positive
+
Top text evidence: cheappricelargeperfectgreat
+
at the current price point , this is a decent shoe horn i was originally going to rate this 3 stars . however , for the current price of $ 7 . 99 , i think this is a decent shoe horn . it is metal with a silicone covering on the upper part . it is also perfect for young children or adults who do not mind bending down to use a shoe horn . it is certainly better than plastic . this is packaged with a big cheap cinch - tie bag . i have no idea why this is included as probably 30 of these shoe horns could fit in that bag . this horn has the potential to bend because it is not super sturdy . i have a similar one with a wooden handle and that one is all bent just from use . my recommendation if you want a great shoe horn that is sturdier and can be used standing up , is to get this [ [ asin : b01m154sed 21 " heavy duty one ] ] for the current price of $ 20 . 99 plus 5 % off . i own one of these and had i purchased that one first , i would have never ordered any other . do note , however , that it is very large and comes up to one ' s knees but it is fantastic . in summary
+
Top metadata source: features 0.750 quality: strong
+
Explanation: VALUE is predicted as Positive. The main text evidence is "cheap", "price", "large", "perfect", and the strongest metadata source is "features" (0.750).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.50
categories 0.50
numeric 0.00
MATERIAL
features 0.50
categories 0.50
numeric 0.00
QUALITY
features 0.50
categories 0.50
numeric 0.00
APPEARANCE
features 0.50
categories 0.50
numeric 0.00
STYLE
features 0.50
categories 0.50
numeric 0.00
VALUE
features 0.75
categories 0.25
numeric 0.00
+
Example 8
+
Rating: 4 | Category: T-Shirts
+
Good Base Layer This is a comfortable shirt. Ideal as a base layer it is made of soft, stretchy material. It is not too tight. It conforms to the body and keeps you warm and dry. Great for cold weather.
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Negative
+
Top text evidence: tightgoodcomfortablesoftgreat
+
good base layer this is a comfortable shirt . ideal as a base layer it is made of soft , stretchy material . it is not too tight . it conforms to the body and keeps you warm and dry . great for cold weather .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: SIZE is predicted as Negative. The main text evidence is "tight", "good", "comfortable", "soft", and the strongest metadata source is "features" (0.500).
+
+
+
MATERIAL: Positive
+
Top text evidence: softstretchymaterialtightgoodcomfortable
+
good base layer this is a comfortable shirt . ideal as a base layer it is made of soft , stretchy material . it is not too tight . it conforms to the body and keeps you warm and dry . great for cold weather .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: MATERIAL is predicted as Positive. The main text evidence is "soft", "stretchy", "material", "tight", and the strongest metadata source is "features" (0.500).
+
+
+
QUALITY: Not_Mentioned
+
Top text evidence: tightgoodcomfortablesoftgreat
+
good base layer this is a comfortable shirt . ideal as a base layer it is made of soft , stretchy material . it is not too tight . it conforms to the body and keeps you warm and dry . great for cold weather .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: QUALITY is predicted as Not_Mentioned. The main text evidence is "tight", "good", "comfortable", "soft", and the strongest metadata source is "features" (0.500).
+
+
+
APPEARANCE: Not_Mentioned
+
Top text evidence: tightgoodcomfortablesoftgreat
+
good base layer this is a comfortable shirt . ideal as a base layer it is made of soft , stretchy material . it is not too tight . it conforms to the body and keeps you warm and dry . great for cold weather .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: APPEARANCE is predicted as Not_Mentioned. The main text evidence is "tight", "good", "comfortable", "soft", and the strongest metadata source is "features" (0.500).
+
+
+
STYLE: Not_Mentioned
+
Top text evidence: shirttightgoodcomfortablesoftgreat
+
good base layer this is a comfortable shirt . ideal as a base layer it is made of soft , stretchy material . it is not too tight . it conforms to the body and keeps you warm and dry . great for cold weather .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: STYLE is predicted as Not_Mentioned. The main text evidence is "shirt", "tight", "good", "comfortable", and the strongest metadata source is "features" (0.500).
+
+
+
VALUE: Not_Mentioned
+
Top text evidence: tightgoodcomfortablesoftgreat
+
good base layer this is a comfortable shirt . ideal as a base layer it is made of soft , stretchy material . it is not too tight . it conforms to the body and keeps you warm and dry . great for cold weather .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: VALUE is predicted as Not_Mentioned. The main text evidence is "tight", "good", "comfortable", "soft", and the strongest metadata source is "features" (0.500).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.50
categories 0.50
numeric 0.00
MATERIAL
features 0.50
categories 0.25
numeric 0.25
QUALITY
features 0.50
categories 0.50
numeric 0.00
APPEARANCE
features 0.50
categories 0.50
numeric 0.00
STYLE
features 0.50
categories 0.50
numeric 0.00
VALUE
features 0.50
categories 0.25
numeric 0.25
+
Example 9
+
Rating: 5 | Category: Fashion Sneakers
+
problem for people with a high instep i love the softness and flexibility of this shoe. i have a high instep, and these shoes have elastic laces. i ordered a wide (i do not have a wide foot) in order to not have the elastic laces cut off my circulation. you can cut the laces out and put in regular laces. shoes would look cute with pink, yellow, or orange laces. red even! feels good in my arch, and pretty comfy overall.
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Negative
+
Top text evidence: lovegood
+
problem for people with a high instep i love the softness and flexibility of this shoe . i have a high instep , and these shoes have elastic laces . i ordered a wide ( i do not have a wide foot ) in order to not have the elastic laces cut off my circulation . you can cut the laces out and put in regular laces . shoes would look cute with pink , yellow , or orange laces . red even ! feels good in my arch , and pretty comfy overall .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: SIZE is predicted as Negative. The main text evidence is "love", "good", and the strongest metadata source is "features" (0.500).
+
+
+
MATERIAL: Negative
+
Top text evidence: lovegood
+
problem for people with a high instep i love the softness and flexibility of this shoe . i have a high instep , and these shoes have elastic laces . i ordered a wide ( i do not have a wide foot ) in order to not have the elastic laces cut off my circulation . you can cut the laces out and put in regular laces . shoes would look cute with pink , yellow , or orange laces . red even ! feels good in my arch , and pretty comfy overall .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: MATERIAL is predicted as Negative. The main text evidence is "love", "good", and the strongest metadata source is "features" (0.500).
+
+
+
QUALITY: Not_Mentioned
+
Top text evidence: lovegood
+
problem for people with a high instep i love the softness and flexibility of this shoe . i have a high instep , and these shoes have elastic laces . i ordered a wide ( i do not have a wide foot ) in order to not have the elastic laces cut off my circulation . you can cut the laces out and put in regular laces . shoes would look cute with pink , yellow , or orange laces . red even ! feels good in my arch , and pretty comfy overall .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: QUALITY is predicted as Not_Mentioned. The main text evidence is "love", "good", and the strongest metadata source is "features" (0.500).
+
+
+
APPEARANCE: Not_Mentioned
+
Top text evidence: lookcutelovegood
+
problem for people with a high instep i love the softness and flexibility of this shoe . i have a high instep , and these shoes have elastic laces . i ordered a wide ( i do not have a wide foot ) in order to not have the elastic laces cut off my circulation . you can cut the laces out and put in regular laces . shoes would look cute with pink , yellow , or orange laces . red even ! feels good in my arch , and pretty comfy overall .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: APPEARANCE is predicted as Not_Mentioned. The main text evidence is "look", "cute", "love", "good", and the strongest metadata source is "features" (0.500).
+
+
+
STYLE: Negative
+
Top text evidence: lovegood
+
problem for people with a high instep i love the softness and flexibility of this shoe . i have a high instep , and these shoes have elastic laces . i ordered a wide ( i do not have a wide foot ) in order to not have the elastic laces cut off my circulation . you can cut the laces out and put in regular laces . shoes would look cute with pink , yellow , or orange laces . red even ! feels good in my arch , and pretty comfy overall .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: STYLE is predicted as Negative. The main text evidence is "love", "good", and the strongest metadata source is "features" (0.500).
+
+
+
VALUE: Not_Mentioned
+
Top text evidence: lovegood
+
problem for people with a high instep i love the softness and flexibility of this shoe . i have a high instep , and these shoes have elastic laces . i ordered a wide ( i do not have a wide foot ) in order to not have the elastic laces cut off my circulation . you can cut the laces out and put in regular laces . shoes would look cute with pink , yellow , or orange laces . red even ! feels good in my arch , and pretty comfy overall .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: VALUE is predicted as Not_Mentioned. The main text evidence is "love", "good", and the strongest metadata source is "features" (0.500).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.50
categories 0.50
numeric 0.00
MATERIAL
features 0.50
categories 0.50
numeric 0.00
QUALITY
features 0.50
categories 0.50
numeric 0.00
APPEARANCE
features 0.50
categories 0.50
numeric 0.00
STYLE
features 0.50
categories 0.50
numeric 0.00
VALUE
features 0.50
categories 0.50
numeric 0.00
+
Example 10
+
Rating: 5 | Category: Board Shorts
+
Cool, relaxed comfort The Kanu Surf Women's plus size Marina solid stretch Boardshort is perfect for lounging around the house or walking the dog. It is exceptionally cool during the summer and has that extra stretch for comfort. Also, like the elastic waistband in the back.
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Not_Mentioned
+
Top text evidence: sizeperfect
+
cool , relaxed comfort the kanu surf women ' s plus size marina solid stretch boardshort is perfect for lounging around the house or walking the dog . it is exceptionally cool during the summer and has that extra stretch for comfort . also , like the elastic waistband in the back .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: SIZE is predicted as Not_Mentioned. The main text evidence is "size", "perfect", and the strongest metadata source is "features" (0.500).
+
+
+
MATERIAL: Positive
+
Top text evidence: stretchperfect
+
cool , relaxed comfort the kanu surf women ' s plus size marina solid stretch boardshort is perfect for lounging around the house or walking the dog . it is exceptionally cool during the summer and has that extra stretch for comfort . also , like the elastic waistband in the back .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: MATERIAL is predicted as Positive. The main text evidence is "stretch", "perfect", and the strongest metadata source is "features" (0.500).
+
+
+
QUALITY: Positive
+
Top text evidence: perfect
+
cool , relaxed comfort the kanu surf women ' s plus size marina solid stretch boardshort is perfect for lounging around the house or walking the dog . it is exceptionally cool during the summer and has that extra stretch for comfort . also , like the elastic waistband in the back .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: QUALITY is predicted as Positive. The main text evidence is "perfect", and the strongest metadata source is "features" (0.500).
+
+
+
APPEARANCE: Not_Mentioned
+
Top text evidence: perfect
+
cool , relaxed comfort the kanu surf women ' s plus size marina solid stretch boardshort is perfect for lounging around the house or walking the dog . it is exceptionally cool during the summer and has that extra stretch for comfort . also , like the elastic waistband in the back .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: APPEARANCE is predicted as Not_Mentioned. The main text evidence is "perfect", and the strongest metadata source is "features" (0.500).
+
+
+
STYLE: Not_Mentioned
+
Top text evidence: perfect
+
cool , relaxed comfort the kanu surf women ' s plus size marina solid stretch boardshort is perfect for lounging around the house or walking the dog . it is exceptionally cool during the summer and has that extra stretch for comfort . also , like the elastic waistband in the back .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: STYLE is predicted as Not_Mentioned. The main text evidence is "perfect", and the strongest metadata source is "features" (0.500).
+
+
+
VALUE: Not_Mentioned
+
Top text evidence: perfect
+
cool , relaxed comfort the kanu surf women ' s plus size marina solid stretch boardshort is perfect for lounging around the house or walking the dog . it is exceptionally cool during the summer and has that extra stretch for comfort . also , like the elastic waistband in the back .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: VALUE is predicted as Not_Mentioned. The main text evidence is "perfect", and the strongest metadata source is "features" (0.500).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.50
categories 0.50
numeric 0.00
MATERIAL
features 0.50
categories 0.50
numeric 0.00
QUALITY
features 0.50
categories 0.50
numeric 0.00
APPEARANCE
features 0.50
categories 0.50
numeric 0.00
STYLE
features 0.50
categories 0.50
numeric 0.00
VALUE
features 0.50
categories 0.50
numeric 0.00
+
Aspect-Level Sentiment with Metadata Fusion: Explanations
+Highlights show the strongest text evidence for each aspect. green = Positive, red = Negative, grey = Not_Mentioned. Metadata rows show which source the model attends to for each aspect.
+Example 1
+
Rating: 1 | Category: Strands
+
Bad quality control I ordered despite all the bad reviews. Well that didn’t work as it was just pack in a baggie as like most of the reviews state. Then the blue and white flowers with charms were all attached backwards. I am in the process of returning it. I will not be asking for an exchange as I do not wish to keep returning this item until I get a good one. So very sad as this could have been a beautiful necklace. Plus with as expensive as this is you would think it would have better packaging. I have bought for much cheaper with nice packaging. Unfortunately I will not be buying any more of this brand as it had put a bad taste in my mouth. Do better!
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Negative
+
Top text evidence: badgoodbeautifulnice
+
bad quality control i ordered despite all the bad reviews . well that didn ’ t work as it was just pack in a baggie as like most of the reviews state . then the blue and white flowers with charms were all attached backwards . i am in the process of returning it . i will not be asking for an exchange as i do not wish to keep returning this item until i get a good one . so very sad as this could have been a beautiful necklace . plus with as expensive as this is you would think it would have better packaging . i have bought for much cheaper with nice packaging . unfortunately i will not be buying any more of this brand as it had put a bad taste in my mouth . do better !
+
Top metadata source: features 0.500 quality: strong
+
Explanation: SIZE is predicted as Negative. The main text evidence is "bad", "good", "beautiful", "nice", and the strongest metadata source is "features" (0.500).
+
+
+
MATERIAL: Negative
+
Top text evidence: badgoodbeautifulnice
+
bad quality control i ordered despite all the bad reviews . well that didn ’ t work as it was just pack in a baggie as like most of the reviews state . then the blue and white flowers with charms were all attached backwards . i am in the process of returning it . i will not be asking for an exchange as i do not wish to keep returning this item until i get a good one . so very sad as this could have been a beautiful necklace . plus with as expensive as this is you would think it would have better packaging . i have bought for much cheaper with nice packaging . unfortunately i will not be buying any more of this brand as it had put a bad taste in my mouth . do better !
+
Top metadata source: features 0.500 quality: strong
+
Explanation: MATERIAL is predicted as Negative. The main text evidence is "bad", "good", "beautiful", "nice", and the strongest metadata source is "features" (0.500).
+
+
+
QUALITY: Negative
+
Top text evidence: qualitybadgoodbeautifulnice
+
bad quality control i ordered despite all the bad reviews . well that didn ’ t work as it was just pack in a baggie as like most of the reviews state . then the blue and white flowers with charms were all attached backwards . i am in the process of returning it . i will not be asking for an exchange as i do not wish to keep returning this item until i get a good one . so very sad as this could have been a beautiful necklace . plus with as expensive as this is you would think it would have better packaging . i have bought for much cheaper with nice packaging . unfortunately i will not be buying any more of this brand as it had put a bad taste in my mouth . do better !
+
Top metadata source: features 0.500 quality: strong
+
Explanation: QUALITY is predicted as Negative. The main text evidence is "quality", "bad", "good", "beautiful", and the strongest metadata source is "features" (0.500).
+
+
+
APPEARANCE: Positive
+
Top text evidence: beautifulbadgoodnice
+
bad quality control i ordered despite all the bad reviews . well that didn ’ t work as it was just pack in a baggie as like most of the reviews state . then the blue and white flowers with charms were all attached backwards . i am in the process of returning it . i will not be asking for an exchange as i do not wish to keep returning this item until i get a good one . so very sad as this could have been a beautiful necklace . plus with as expensive as this is you would think it would have better packaging . i have bought for much cheaper with nice packaging . unfortunately i will not be buying any more of this brand as it had put a bad taste in my mouth . do better !
+
Top metadata source: features 0.500 quality: strong
+
Explanation: APPEARANCE is predicted as Positive. The main text evidence is "beautiful", "bad", "good", "nice", and the strongest metadata source is "features" (0.500).
+
+
+
STYLE: Negative
+
Top text evidence: badgoodbeautifulnice
+
bad quality control i ordered despite all the bad reviews . well that didn ’ t work as it was just pack in a baggie as like most of the reviews state . then the blue and white flowers with charms were all attached backwards . i am in the process of returning it . i will not be asking for an exchange as i do not wish to keep returning this item until i get a good one . so very sad as this could have been a beautiful necklace . plus with as expensive as this is you would think it would have better packaging . i have bought for much cheaper with nice packaging . unfortunately i will not be buying any more of this brand as it had put a bad taste in my mouth . do better !
+
Top metadata source: features 0.500 quality: strong
+
Explanation: STYLE is predicted as Negative. The main text evidence is "bad", "good", "beautiful", "nice", and the strongest metadata source is "features" (0.500).
+
+
+
VALUE: Negative
+
Top text evidence: expensivebadgoodbeautifulnice
+
bad quality control i ordered despite all the bad reviews . well that didn ’ t work as it was just pack in a baggie as like most of the reviews state . then the blue and white flowers with charms were all attached backwards . i am in the process of returning it . i will not be asking for an exchange as i do not wish to keep returning this item until i get a good one . so very sad as this could have been a beautiful necklace . plus with as expensive as this is you would think it would have better packaging . i have bought for much cheaper with nice packaging . unfortunately i will not be buying any more of this brand as it had put a bad taste in my mouth . do better !
+
Top metadata source: features 0.500 quality: strong
+
Explanation: VALUE is predicted as Negative. The main text evidence is "expensive", "bad", "good", "beautiful", and the strongest metadata source is "features" (0.500).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.50
categories 0.25
numeric 0.25
MATERIAL
features 0.50
categories 0.25
numeric 0.25
QUALITY
features 0.50
categories 0.25
numeric 0.25
APPEARANCE
features 0.50
categories 0.25
numeric 0.25
STYLE
features 0.50
categories 0.25
numeric 0.25
VALUE
features 0.50
categories 0.25
numeric 0.25
+
Example 2
+
Rating: 1 | Category: Rash Guard Shirts
+
Very small for size and returned Too tight for size and Iborderwd extra large.
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Negative
+
Top text evidence: smalltightlargesizereturned
+
very small for size and returned too tight for size and iborderwd extra large .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: SIZE is predicted as Negative. The main text evidence is "small", "tight", "large", "size", and the strongest metadata source is "features" (0.500).
+
+
+
MATERIAL: Not_Mentioned
+
Top text evidence: smalltightreturnedlarge
+
very small for size and returned too tight for size and iborderwd extra large .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: MATERIAL is predicted as Not_Mentioned. The main text evidence is "small", "tight", "returned", "large", and the strongest metadata source is "features" (0.500).
+
+
+
QUALITY: Not_Mentioned
+
Top text evidence: smalltightreturnedlarge
+
very small for size and returned too tight for size and iborderwd extra large .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: QUALITY is predicted as Not_Mentioned. The main text evidence is "small", "tight", "returned", "large", and the strongest metadata source is "features" (0.500).
+
+
+
APPEARANCE: Not_Mentioned
+
Top text evidence: smalltightreturnedlarge
+
very small for size and returned too tight for size and iborderwd extra large .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: APPEARANCE is predicted as Not_Mentioned. The main text evidence is "small", "tight", "returned", "large", and the strongest metadata source is "features" (0.500).
+
+
+
STYLE: Not_Mentioned
+
Top text evidence: smalltightreturnedlarge
+
very small for size and returned too tight for size and iborderwd extra large .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: STYLE is predicted as Not_Mentioned. The main text evidence is "small", "tight", "returned", "large", and the strongest metadata source is "features" (0.500).
+
+
+
VALUE: Not_Mentioned
+
Top text evidence: smalltightreturnedlarge
+
very small for size and returned too tight for size and iborderwd extra large .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: VALUE is predicted as Not_Mentioned. The main text evidence is "small", "tight", "returned", "large", and the strongest metadata source is "features" (0.500).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.50
categories 0.25
numeric 0.25
MATERIAL
features 0.50
categories 0.25
numeric 0.25
QUALITY
features 0.50
categories 0.25
numeric 0.25
APPEARANCE
features 0.50
categories 0.25
numeric 0.25
STYLE
features 0.50
categories 0.25
numeric 0.25
VALUE
features 0.50
categories 0.25
numeric 0.25
+
Example 3
+
Rating: 2 | Category: Identification
+
Not great Not comfortable to wear. The information portion of the bracelet has very sharp edges. Adjusting the length requires a tool. You can't push down the locking part by hand. So broken clasp after long wait. They did issue a refund without requiring me to return the item
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Negative
+
Top text evidence: lengthgreatcomfortablereturn
+
not great not comfortable to wear . the information portion of the bracelet has very sharp edges . adjusting the length requires a tool . you can ' t push down the locking part by hand . so broken clasp after long wait . they did issue a refund without requiring me to return the item
+
Top metadata source: features 0.750 quality: strong
+
Explanation: SIZE is predicted as Negative. The main text evidence is "length", "great", "comfortable", "return", and the strongest metadata source is "features" (0.750).
+
+
+
MATERIAL: Not_Mentioned
+
Top text evidence: greatcomfortablereturn
+
not great not comfortable to wear . the information portion of the bracelet has very sharp edges . adjusting the length requires a tool . you can ' t push down the locking part by hand . so broken clasp after long wait . they did issue a refund without requiring me to return the item
+
Top metadata source: features 0.500 quality: strong
+
Explanation: MATERIAL is predicted as Not_Mentioned. The main text evidence is "great", "comfortable", "return", and the strongest metadata source is "features" (0.500).
+
+
+
QUALITY: Negative
+
Top text evidence: greatcomfortablereturn
+
not great not comfortable to wear . the information portion of the bracelet has very sharp edges . adjusting the length requires a tool . you can ' t push down the locking part by hand . so broken clasp after long wait . they did issue a refund without requiring me to return the item
+
Top metadata source: features 0.750 quality: strong
+
Explanation: QUALITY is predicted as Negative. The main text evidence is "great", "comfortable", "return", and the strongest metadata source is "features" (0.750).
+
+
+
APPEARANCE: Not_Mentioned
+
Top text evidence: greatcomfortablereturn
+
not great not comfortable to wear . the information portion of the bracelet has very sharp edges . adjusting the length requires a tool . you can ' t push down the locking part by hand . so broken clasp after long wait . they did issue a refund without requiring me to return the item
+
Top metadata source: features 0.750 quality: strong
+
Explanation: APPEARANCE is predicted as Not_Mentioned. The main text evidence is "great", "comfortable", "return", and the strongest metadata source is "features" (0.750).
+
+
+
STYLE: Not_Mentioned
+
Top text evidence: greatcomfortablereturn
+
not great not comfortable to wear . the information portion of the bracelet has very sharp edges . adjusting the length requires a tool . you can ' t push down the locking part by hand . so broken clasp after long wait . they did issue a refund without requiring me to return the item
+
Top metadata source: features 0.750 quality: strong
+
Explanation: STYLE is predicted as Not_Mentioned. The main text evidence is "great", "comfortable", "return", and the strongest metadata source is "features" (0.750).
+
+
+
VALUE: Negative
+
Top text evidence: greatcomfortablereturn
+
not great not comfortable to wear . the information portion of the bracelet has very sharp edges . adjusting the length requires a tool . you can ' t push down the locking part by hand . so broken clasp after long wait . they did issue a refund without requiring me to return the item
+
Top metadata source: features 0.500 quality: strong
+
Explanation: VALUE is predicted as Negative. The main text evidence is "great", "comfortable", "return", and the strongest metadata source is "features" (0.500).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.75
categories 0.25
numeric 0.00
MATERIAL
features 0.50
categories 0.25
numeric 0.25
QUALITY
features 0.75
categories 0.25
numeric 0.00
APPEARANCE
features 0.75
categories 0.25
numeric 0.00
STYLE
features 0.75
categories 0.25
numeric 0.00
VALUE
features 0.50
categories 0.25
numeric 0.25
+
Example 4
+
Rating: 2 | Category: Wallets
+
Two Stars loved it until the pin fell out after having it only a month
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Not_Mentioned
+
Top text evidence: loved
+
two stars loved it until the pin fell out after having it only a month
+
Top metadata source: features 0.750 quality: moderate
+
Explanation: SIZE is predicted as Not_Mentioned. The main text evidence is "loved", and the strongest metadata source is "features" (0.750).
+
+
+
MATERIAL: Not_Mentioned
+
Top text evidence: loved
+
two stars loved it until the pin fell out after having it only a month
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: MATERIAL is predicted as Not_Mentioned. The main text evidence is "loved", and the strongest metadata source is "features" (0.500).
+
+
+
QUALITY: Not_Mentioned
+
Top text evidence: loved
+
two stars loved it until the pin fell out after having it only a month
+
Top metadata source: features 0.750 quality: moderate
+
Explanation: QUALITY is predicted as Not_Mentioned. The main text evidence is "loved", and the strongest metadata source is "features" (0.750).
+
+
+
APPEARANCE: Not_Mentioned
+
Top text evidence: loved
+
two stars loved it until the pin fell out after having it only a month
+
Top metadata source: features 0.750 quality: moderate
+
Explanation: APPEARANCE is predicted as Not_Mentioned. The main text evidence is "loved", and the strongest metadata source is "features" (0.750).
+
+
+
STYLE: Not_Mentioned
+
Top text evidence: loved
+
two stars loved it until the pin fell out after having it only a month
+
Top metadata source: features 0.750 quality: moderate
+
Explanation: STYLE is predicted as Not_Mentioned. The main text evidence is "loved", and the strongest metadata source is "features" (0.750).
+
+
+
VALUE: Not_Mentioned
+
Top text evidence: loved
+
two stars loved it until the pin fell out after having it only a month
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: VALUE is predicted as Not_Mentioned. The main text evidence is "loved", and the strongest metadata source is "features" (0.500).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.75
categories 0.25
numeric 0.00
MATERIAL
features 0.50
categories 0.25
numeric 0.25
QUALITY
features 0.75
categories 0.25
numeric 0.00
APPEARANCE
features 0.75
categories 0.25
numeric 0.00
STYLE
features 0.75
categories 0.25
numeric 0.00
VALUE
features 0.50
categories 0.25
numeric 0.25
+
Example 5
+
Rating: 3 | Category: Cocktail
+
Okay Not the best quality, pretty skimpy
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Not_Mentioned
+
okay not the best quality , pretty skimpy
+
Top metadata source: features 0.500 quality: weak
+
Explanation: SIZE is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.500).
+
+
+
MATERIAL: Not_Mentioned
+
okay not the best quality , pretty skimpy
+
Top metadata source: features 0.500 quality: weak
+
Explanation: MATERIAL is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.500).
+
+
+
QUALITY: Not_Mentioned
+
Top text evidence: quality
+
okay not the best quality , pretty skimpy
+
Top metadata source: features 0.750 quality: moderate
+
Explanation: QUALITY is predicted as Not_Mentioned. The main text evidence is "quality", and the strongest metadata source is "features" (0.750).
+
+
+
APPEARANCE: Not_Mentioned
+
okay not the best quality , pretty skimpy
+
Top metadata source: features 0.750 quality: weak
+
Explanation: APPEARANCE is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.750).
+
+
+
STYLE: Not_Mentioned
+
okay not the best quality , pretty skimpy
+
Top metadata source: features 0.750 quality: weak
+
Explanation: STYLE is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.750).
+
+
+
VALUE: Not_Mentioned
+
okay not the best quality , pretty skimpy
+
Top metadata source: features 0.500 quality: weak
+
Explanation: VALUE is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.500).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.50
categories 0.25
numeric 0.25
MATERIAL
features 0.50
categories 0.25
numeric 0.25
QUALITY
features 0.75
categories 0.25
numeric 0.00
APPEARANCE
features 0.75
categories 0.25
numeric 0.00
STYLE
features 0.75
categories 0.25
numeric 0.00
VALUE
features 0.50
categories 0.25
numeric 0.25
+
Example 6
+
Rating: 3 | Category: Aprons
+
Okay don't have very much to say about this on ipad version, other than its okay
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Not_Mentioned
+
okay don ' t have very much to say about this on ipad version , other than its okay
+
Top metadata source: features 0.750 quality: weak
+
Explanation: SIZE is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.750).
+
+
+
MATERIAL: Not_Mentioned
+
okay don ' t have very much to say about this on ipad version , other than its okay
+
Top metadata source: features 0.750 quality: weak
+
Explanation: MATERIAL is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.750).
+
+
+
QUALITY: Not_Mentioned
+
okay don ' t have very much to say about this on ipad version , other than its okay
+
Top metadata source: features 0.750 quality: weak
+
Explanation: QUALITY is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.750).
+
+
+
APPEARANCE: Not_Mentioned
+
okay don ' t have very much to say about this on ipad version , other than its okay
+
Top metadata source: features 0.750 quality: weak
+
Explanation: APPEARANCE is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.750).
+
+
+
STYLE: Not_Mentioned
+
okay don ' t have very much to say about this on ipad version , other than its okay
+
Top metadata source: features 0.750 quality: weak
+
Explanation: STYLE is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.750).
+
+
+
VALUE: Not_Mentioned
+
okay don ' t have very much to say about this on ipad version , other than its okay
+
Top metadata source: features 0.749 quality: weak
+
Explanation: VALUE is predicted as Not_Mentioned. The main text evidence is no strong text token, and the strongest metadata source is "features" (0.749).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.75
categories 0.25
numeric 0.00
MATERIAL
features 0.75
categories 0.25
numeric 0.00
QUALITY
features 0.75
categories 0.25
numeric 0.00
APPEARANCE
features 0.75
categories 0.25
numeric 0.00
STYLE
features 0.75
categories 0.25
numeric 0.00
VALUE
features 0.75
categories 0.25
numeric 0.00
+
Example 7
+
Rating: 4 | Category: Shoe Horns & Boot Jacks
+
At the current price point, this is a decent shoe horn I was originally going to rate this 3 stars. However, for the current price of $7.99, I think this is a decent shoe horn. It is metal with a silicone covering on the upper part. It is also perfect for young children or adults who do not mind bending down to use a shoe horn. It is certainly better than plastic. This is packaged with a big cheap cinch-tie bag. I have no idea why this is included as probably 30 of these shoe horns could fit in that bag. This horn has the potential to bend because it is not super sturdy. I have a similar one with a wooden handle and that one is all bent just from use. My recommendation if you want a great shoe horn that is sturdier and can be used standing up, is to get this [[ASIN:B01M154SED 21" heavy duty one]] for the current price of $20.99 plus 5% off. I own one of these and had I purchased that one first, I would have never ordered any other. Do note, however, that it is very large and comes up to one's knees but it is fantastic. In summary, this one is decent and functional at the low price point but for something more sturdy and that will last longer, look into the other one I recommended.
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Negative
+
Top text evidence: largebigfitperfectcheapgreat
+
at the current price point , this is a decent shoe horn i was originally going to rate this 3 stars . however , for the current price of $ 7 . 99 , i think this is a decent shoe horn . it is metal with a silicone covering on the upper part . it is also perfect for young children or adults who do not mind bending down to use a shoe horn . it is certainly better than plastic . this is packaged with a big cheap cinch - tie bag . i have no idea why this is included as probably 30 of these shoe horns could fit in that bag . this horn has the potential to bend because it is not super sturdy . i have a similar one with a wooden handle and that one is all bent just from use . my recommendation if you want a great shoe horn that is sturdier and can be used standing up , is to get this [ [ asin : b01m154sed 21 " heavy duty one ] ] for the current price of $ 20 . 99 plus 5 % off . i own one of these and had i purchased that one first , i would have never ordered any other . do note , however , that it is very large and comes up to one ' s knees but it is fantastic . in summary
+
Top metadata source: features 0.500 quality: strong
+
Explanation: SIZE is predicted as Negative. The main text evidence is "large", "big", "fit", "perfect", and the strongest metadata source is "features" (0.500).
+
+
+
MATERIAL: Negative
+
Top text evidence: largeperfectcheapgreat
+
at the current price point , this is a decent shoe horn i was originally going to rate this 3 stars . however , for the current price of $ 7 . 99 , i think this is a decent shoe horn . it is metal with a silicone covering on the upper part . it is also perfect for young children or adults who do not mind bending down to use a shoe horn . it is certainly better than plastic . this is packaged with a big cheap cinch - tie bag . i have no idea why this is included as probably 30 of these shoe horns could fit in that bag . this horn has the potential to bend because it is not super sturdy . i have a similar one with a wooden handle and that one is all bent just from use . my recommendation if you want a great shoe horn that is sturdier and can be used standing up , is to get this [ [ asin : b01m154sed 21 " heavy duty one ] ] for the current price of $ 20 . 99 plus 5 % off . i own one of these and had i purchased that one first , i would have never ordered any other . do note , however , that it is very large and comes up to one ' s knees but it is fantastic . in summary
+
Top metadata source: features 0.500 quality: strong
+
Explanation: MATERIAL is predicted as Negative. The main text evidence is "large", "perfect", "cheap", "great", and the strongest metadata source is "features" (0.500).
+
+
+
QUALITY: Positive
+
Top text evidence: cheaplargeperfectgreat
+
at the current price point , this is a decent shoe horn i was originally going to rate this 3 stars . however , for the current price of $ 7 . 99 , i think this is a decent shoe horn . it is metal with a silicone covering on the upper part . it is also perfect for young children or adults who do not mind bending down to use a shoe horn . it is certainly better than plastic . this is packaged with a big cheap cinch - tie bag . i have no idea why this is included as probably 30 of these shoe horns could fit in that bag . this horn has the potential to bend because it is not super sturdy . i have a similar one with a wooden handle and that one is all bent just from use . my recommendation if you want a great shoe horn that is sturdier and can be used standing up , is to get this [ [ asin : b01m154sed 21 " heavy duty one ] ] for the current price of $ 20 . 99 plus 5 % off . i own one of these and had i purchased that one first , i would have never ordered any other . do note , however , that it is very large and comes up to one ' s knees but it is fantastic . in summary
+
Top metadata source: features 0.500 quality: strong
+
Explanation: QUALITY is predicted as Positive. The main text evidence is "cheap", "large", "perfect", "great", and the strongest metadata source is "features" (0.500).
+
+
+
APPEARANCE: Not_Mentioned
+
Top text evidence: largeperfectcheapgreat
+
at the current price point , this is a decent shoe horn i was originally going to rate this 3 stars . however , for the current price of $ 7 . 99 , i think this is a decent shoe horn . it is metal with a silicone covering on the upper part . it is also perfect for young children or adults who do not mind bending down to use a shoe horn . it is certainly better than plastic . this is packaged with a big cheap cinch - tie bag . i have no idea why this is included as probably 30 of these shoe horns could fit in that bag . this horn has the potential to bend because it is not super sturdy . i have a similar one with a wooden handle and that one is all bent just from use . my recommendation if you want a great shoe horn that is sturdier and can be used standing up , is to get this [ [ asin : b01m154sed 21 " heavy duty one ] ] for the current price of $ 20 . 99 plus 5 % off . i own one of these and had i purchased that one first , i would have never ordered any other . do note , however , that it is very large and comes up to one ' s knees but it is fantastic . in summary
+
Top metadata source: features 0.500 quality: strong
+
Explanation: APPEARANCE is predicted as Not_Mentioned. The main text evidence is "large", "perfect", "cheap", "great", and the strongest metadata source is "features" (0.500).
+
+
+
STYLE: Not_Mentioned
+
Top text evidence: largeperfectcheapgreat
+
at the current price point , this is a decent shoe horn i was originally going to rate this 3 stars . however , for the current price of $ 7 . 99 , i think this is a decent shoe horn . it is metal with a silicone covering on the upper part . it is also perfect for young children or adults who do not mind bending down to use a shoe horn . it is certainly better than plastic . this is packaged with a big cheap cinch - tie bag . i have no idea why this is included as probably 30 of these shoe horns could fit in that bag . this horn has the potential to bend because it is not super sturdy . i have a similar one with a wooden handle and that one is all bent just from use . my recommendation if you want a great shoe horn that is sturdier and can be used standing up , is to get this [ [ asin : b01m154sed 21 " heavy duty one ] ] for the current price of $ 20 . 99 plus 5 % off . i own one of these and had i purchased that one first , i would have never ordered any other . do note , however , that it is very large and comes up to one ' s knees but it is fantastic . in summary
+
Top metadata source: features 0.500 quality: strong
+
Explanation: STYLE is predicted as Not_Mentioned. The main text evidence is "large", "perfect", "cheap", "great", and the strongest metadata source is "features" (0.500).
+
+
+
VALUE: Positive
+
Top text evidence: cheappricelargeperfectgreat
+
at the current price point , this is a decent shoe horn i was originally going to rate this 3 stars . however , for the current price of $ 7 . 99 , i think this is a decent shoe horn . it is metal with a silicone covering on the upper part . it is also perfect for young children or adults who do not mind bending down to use a shoe horn . it is certainly better than plastic . this is packaged with a big cheap cinch - tie bag . i have no idea why this is included as probably 30 of these shoe horns could fit in that bag . this horn has the potential to bend because it is not super sturdy . i have a similar one with a wooden handle and that one is all bent just from use . my recommendation if you want a great shoe horn that is sturdier and can be used standing up , is to get this [ [ asin : b01m154sed 21 " heavy duty one ] ] for the current price of $ 20 . 99 plus 5 % off . i own one of these and had i purchased that one first , i would have never ordered any other . do note , however , that it is very large and comes up to one ' s knees but it is fantastic . in summary
+
Top metadata source: features 0.750 quality: strong
+
Explanation: VALUE is predicted as Positive. The main text evidence is "cheap", "price", "large", "perfect", and the strongest metadata source is "features" (0.750).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.50
categories 0.50
numeric 0.00
MATERIAL
features 0.50
categories 0.50
numeric 0.00
QUALITY
features 0.50
categories 0.50
numeric 0.00
APPEARANCE
features 0.50
categories 0.50
numeric 0.00
STYLE
features 0.50
categories 0.50
numeric 0.00
VALUE
features 0.75
categories 0.25
numeric 0.00
+
Example 8
+
Rating: 4 | Category: T-Shirts
+
Good Base Layer This is a comfortable shirt. Ideal as a base layer it is made of soft, stretchy material. It is not too tight. It conforms to the body and keeps you warm and dry. Great for cold weather.
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Negative
+
Top text evidence: tightgoodcomfortablesoftgreat
+
good base layer this is a comfortable shirt . ideal as a base layer it is made of soft , stretchy material . it is not too tight . it conforms to the body and keeps you warm and dry . great for cold weather .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: SIZE is predicted as Negative. The main text evidence is "tight", "good", "comfortable", "soft", and the strongest metadata source is "features" (0.500).
+
+
+
MATERIAL: Positive
+
Top text evidence: softstretchymaterialtightgoodcomfortable
+
good base layer this is a comfortable shirt . ideal as a base layer it is made of soft , stretchy material . it is not too tight . it conforms to the body and keeps you warm and dry . great for cold weather .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: MATERIAL is predicted as Positive. The main text evidence is "soft", "stretchy", "material", "tight", and the strongest metadata source is "features" (0.500).
+
+
+
QUALITY: Not_Mentioned
+
Top text evidence: tightgoodcomfortablesoftgreat
+
good base layer this is a comfortable shirt . ideal as a base layer it is made of soft , stretchy material . it is not too tight . it conforms to the body and keeps you warm and dry . great for cold weather .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: QUALITY is predicted as Not_Mentioned. The main text evidence is "tight", "good", "comfortable", "soft", and the strongest metadata source is "features" (0.500).
+
+
+
APPEARANCE: Not_Mentioned
+
Top text evidence: tightgoodcomfortablesoftgreat
+
good base layer this is a comfortable shirt . ideal as a base layer it is made of soft , stretchy material . it is not too tight . it conforms to the body and keeps you warm and dry . great for cold weather .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: APPEARANCE is predicted as Not_Mentioned. The main text evidence is "tight", "good", "comfortable", "soft", and the strongest metadata source is "features" (0.500).
+
+
+
STYLE: Not_Mentioned
+
Top text evidence: shirttightgoodcomfortablesoftgreat
+
good base layer this is a comfortable shirt . ideal as a base layer it is made of soft , stretchy material . it is not too tight . it conforms to the body and keeps you warm and dry . great for cold weather .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: STYLE is predicted as Not_Mentioned. The main text evidence is "shirt", "tight", "good", "comfortable", and the strongest metadata source is "features" (0.500).
+
+
+
VALUE: Not_Mentioned
+
Top text evidence: tightgoodcomfortablesoftgreat
+
good base layer this is a comfortable shirt . ideal as a base layer it is made of soft , stretchy material . it is not too tight . it conforms to the body and keeps you warm and dry . great for cold weather .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: VALUE is predicted as Not_Mentioned. The main text evidence is "tight", "good", "comfortable", "soft", and the strongest metadata source is "features" (0.500).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.50
categories 0.50
numeric 0.00
MATERIAL
features 0.50
categories 0.25
numeric 0.25
QUALITY
features 0.50
categories 0.50
numeric 0.00
APPEARANCE
features 0.50
categories 0.50
numeric 0.00
STYLE
features 0.50
categories 0.50
numeric 0.00
VALUE
features 0.50
categories 0.25
numeric 0.25
+
Example 9
+
Rating: 5 | Category: Fashion Sneakers
+
problem for people with a high instep i love the softness and flexibility of this shoe. i have a high instep, and these shoes have elastic laces. i ordered a wide (i do not have a wide foot) in order to not have the elastic laces cut off my circulation. you can cut the laces out and put in regular laces. shoes would look cute with pink, yellow, or orange laces. red even! feels good in my arch, and pretty comfy overall.
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Negative
+
Top text evidence: lovegood
+
problem for people with a high instep i love the softness and flexibility of this shoe . i have a high instep , and these shoes have elastic laces . i ordered a wide ( i do not have a wide foot ) in order to not have the elastic laces cut off my circulation . you can cut the laces out and put in regular laces . shoes would look cute with pink , yellow , or orange laces . red even ! feels good in my arch , and pretty comfy overall .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: SIZE is predicted as Negative. The main text evidence is "love", "good", and the strongest metadata source is "features" (0.500).
+
+
+
MATERIAL: Negative
+
Top text evidence: lovegood
+
problem for people with a high instep i love the softness and flexibility of this shoe . i have a high instep , and these shoes have elastic laces . i ordered a wide ( i do not have a wide foot ) in order to not have the elastic laces cut off my circulation . you can cut the laces out and put in regular laces . shoes would look cute with pink , yellow , or orange laces . red even ! feels good in my arch , and pretty comfy overall .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: MATERIAL is predicted as Negative. The main text evidence is "love", "good", and the strongest metadata source is "features" (0.500).
+
+
+
QUALITY: Not_Mentioned
+
Top text evidence: lovegood
+
problem for people with a high instep i love the softness and flexibility of this shoe . i have a high instep , and these shoes have elastic laces . i ordered a wide ( i do not have a wide foot ) in order to not have the elastic laces cut off my circulation . you can cut the laces out and put in regular laces . shoes would look cute with pink , yellow , or orange laces . red even ! feels good in my arch , and pretty comfy overall .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: QUALITY is predicted as Not_Mentioned. The main text evidence is "love", "good", and the strongest metadata source is "features" (0.500).
+
+
+
APPEARANCE: Not_Mentioned
+
Top text evidence: lookcutelovegood
+
problem for people with a high instep i love the softness and flexibility of this shoe . i have a high instep , and these shoes have elastic laces . i ordered a wide ( i do not have a wide foot ) in order to not have the elastic laces cut off my circulation . you can cut the laces out and put in regular laces . shoes would look cute with pink , yellow , or orange laces . red even ! feels good in my arch , and pretty comfy overall .
+
Top metadata source: features 0.500 quality: strong
+
Explanation: APPEARANCE is predicted as Not_Mentioned. The main text evidence is "look", "cute", "love", "good", and the strongest metadata source is "features" (0.500).
+
+
+
STYLE: Negative
+
Top text evidence: lovegood
+
problem for people with a high instep i love the softness and flexibility of this shoe . i have a high instep , and these shoes have elastic laces . i ordered a wide ( i do not have a wide foot ) in order to not have the elastic laces cut off my circulation . you can cut the laces out and put in regular laces . shoes would look cute with pink , yellow , or orange laces . red even ! feels good in my arch , and pretty comfy overall .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: STYLE is predicted as Negative. The main text evidence is "love", "good", and the strongest metadata source is "features" (0.500).
+
+
+
VALUE: Not_Mentioned
+
Top text evidence: lovegood
+
problem for people with a high instep i love the softness and flexibility of this shoe . i have a high instep , and these shoes have elastic laces . i ordered a wide ( i do not have a wide foot ) in order to not have the elastic laces cut off my circulation . you can cut the laces out and put in regular laces . shoes would look cute with pink , yellow , or orange laces . red even ! feels good in my arch , and pretty comfy overall .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: VALUE is predicted as Not_Mentioned. The main text evidence is "love", "good", and the strongest metadata source is "features" (0.500).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.50
categories 0.50
numeric 0.00
MATERIAL
features 0.50
categories 0.50
numeric 0.00
QUALITY
features 0.50
categories 0.50
numeric 0.00
APPEARANCE
features 0.50
categories 0.50
numeric 0.00
STYLE
features 0.50
categories 0.50
numeric 0.00
VALUE
features 0.50
categories 0.50
numeric 0.00
+
Example 10
+
Rating: 5 | Category: Board Shorts
+
Cool, relaxed comfort The Kanu Surf Women's plus size Marina solid stretch Boardshort is perfect for lounging around the house or walking the dog. It is exceptionally cool during the summer and has that extra stretch for comfort. Also, like the elastic waistband in the back.
+
+
Per-aspect prediction, text evidence, and metadata source
+
+
SIZE: Not_Mentioned
+
Top text evidence: sizeperfect
+
cool , relaxed comfort the kanu surf women ' s plus size marina solid stretch boardshort is perfect for lounging around the house or walking the dog . it is exceptionally cool during the summer and has that extra stretch for comfort . also , like the elastic waistband in the back .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: SIZE is predicted as Not_Mentioned. The main text evidence is "size", "perfect", and the strongest metadata source is "features" (0.500).
+
+
+
MATERIAL: Positive
+
Top text evidence: stretchperfect
+
cool , relaxed comfort the kanu surf women ' s plus size marina solid stretch boardshort is perfect for lounging around the house or walking the dog . it is exceptionally cool during the summer and has that extra stretch for comfort . also , like the elastic waistband in the back .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: MATERIAL is predicted as Positive. The main text evidence is "stretch", "perfect", and the strongest metadata source is "features" (0.500).
+
+
+
QUALITY: Positive
+
Top text evidence: perfect
+
cool , relaxed comfort the kanu surf women ' s plus size marina solid stretch boardshort is perfect for lounging around the house or walking the dog . it is exceptionally cool during the summer and has that extra stretch for comfort . also , like the elastic waistband in the back .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: QUALITY is predicted as Positive. The main text evidence is "perfect", and the strongest metadata source is "features" (0.500).
+
+
+
APPEARANCE: Not_Mentioned
+
Top text evidence: perfect
+
cool , relaxed comfort the kanu surf women ' s plus size marina solid stretch boardshort is perfect for lounging around the house or walking the dog . it is exceptionally cool during the summer and has that extra stretch for comfort . also , like the elastic waistband in the back .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: APPEARANCE is predicted as Not_Mentioned. The main text evidence is "perfect", and the strongest metadata source is "features" (0.500).
+
+
+
STYLE: Not_Mentioned
+
Top text evidence: perfect
+
cool , relaxed comfort the kanu surf women ' s plus size marina solid stretch boardshort is perfect for lounging around the house or walking the dog . it is exceptionally cool during the summer and has that extra stretch for comfort . also , like the elastic waistband in the back .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: STYLE is predicted as Not_Mentioned. The main text evidence is "perfect", and the strongest metadata source is "features" (0.500).
+
+
+
VALUE: Not_Mentioned
+
Top text evidence: perfect
+
cool , relaxed comfort the kanu surf women ' s plus size marina solid stretch boardshort is perfect for lounging around the house or walking the dog . it is exceptionally cool during the summer and has that extra stretch for comfort . also , like the elastic waistband in the back .
+
Top metadata source: features 0.500 quality: moderate
+
Explanation: VALUE is predicted as Not_Mentioned. The main text evidence is "perfect", and the strongest metadata source is "features" (0.500).
+
+
Metadata cross-attention (global / averaged)
+
+
Aspect-specific metadata attention
+
SIZE
features 0.50
categories 0.50
numeric 0.00
MATERIAL
features 0.50
categories 0.50
numeric 0.00
QUALITY
features 0.50
categories 0.50
numeric 0.00
APPEARANCE
features 0.50
categories 0.50
numeric 0.00
STYLE
features 0.50
categories 0.50
numeric 0.00
VALUE
features 0.50
categories 0.50
numeric 0.00
+
']
+ for i, (n, raw) in enumerate(zip(norm, meta_attn)):
+ name = token_names[i] if i < len(token_names) else f"meta_{i+1}"
+ h = int(8 + 50 * float(n))
+ parts.append(
+ f'
'
+ f'
'
+ f'
'
+ f'{html_lib.escape(name)}
{float(raw):.3f}
'
+ )
+ parts.append('
']
+ for i, aspect in enumerate(cfg.ASPECTS):
+ if i >= arr.shape[0]:
+ break
+ weights = arr[i]
+ norm = _normalize(weights)
+ parts.append('
')
+ parts.append(f'
{aspect}
')
+ for j, (n, raw) in enumerate(zip(norm, weights)):
+ name = token_names[j] if j < len(token_names) else f"meta_{j+1}"
+ w = int(35 + 75 * float(n))
+ parts.append(
+ f'
'
+ f'{html_lib.escape(name)} {float(raw):.2f}
'
+ )
+ parts.append('
')
+ parts.append('
{html_lib.escape(name)}: '
+ f'{value or "not available"}
'
+ )
+ return '' + "".join(rows) + '
'
+
+
+def build_explanation_html(examples: List[dict], output_path: Path):
+ parts = [
+ "",
+ "ACSA + Meta Fusion Explanations",
+ "",
+ "Aspect-Level Sentiment with Metadata Fusion: Explanations
",
+ ''
+ 'Highlights show the strongest text evidence for each aspect. '
+ 'green = Positive, '
+ 'red = Negative, '
+ 'grey = Not_Mentioned. '
+ 'Metadata rows show which source the model attends to for each aspect.'
+ '
',
+ ]
+ for i, ex in enumerate(examples):
+ parts.append(f'Example {i+1}
')
+ parts.append(f'
Rating: {ex.get("rating", "?")} | Category: {html_lib.escape(str(ex.get("category", "?")))}
')
+ parts.append(f'
{html_lib.escape(ex["text"])}
')
+ parts.append(_render_meta_summary_html(ex.get("meta_summary", {})))
+
+ parts.append('
Per-aspect prediction, text evidence, and metadata source
')
+ token_names = ex.get("meta_token_names")
+ meta_by_aspect = ex.get("meta_attn_by_aspect")
+ for idx, a in enumerate(ex["aspects"]):
+ pred = a["pred_label"]
+ name = cfg.LABEL_NAMES[pred]
+ css = {0: "pred-na", 1: "pred-pos", 2: "pred-neg"}[pred]
+ parts.append('
')
+ parts.append(f'
{a["aspect"]}: {name}')
+
+ if "tokens" in a and "scores" in a:
+ terms = a.get("top_terms") or []
+ chips = "".join(f'
{html_lib.escape(t)}' for t, _ in terms[:6])
+ if chips:
+ parts.append(f'
Top text evidence: {chips}
')
+ tok_html = _render_token_html(a["tokens"], a["scores"], pred)
+ parts.append(f'
{tok_html}
')
+
+ if meta_by_aspect is not None and idx < len(meta_by_aspect):
+ source, weight = _top_meta_source(meta_by_aspect[idx], token_names)
+ else:
+ source, weight = _top_meta_source(ex.get("meta_attn", []), token_names)
+ quality = a.get("evidence_quality", "weak")
+ explanation = a.get("explanation_sentence", "")
+ if source:
+ parts.append(
+ f'
Top metadata source: '
+ f'{html_lib.escape(source)} {weight:.3f} '
+ f'quality: {html_lib.escape(quality)}
'
+ )
+ if explanation:
+ parts.append(
+ f'
Explanation: '
+ f'{html_lib.escape(explanation)}
'
+ )
+ parts.append('
')
+
+ parts.append('
Metadata cross-attention (global / averaged)
')
+ parts.append(_render_meta_bar_html(np.asarray(ex["meta_attn"]), token_names))
+ if meta_by_aspect is not None:
+ parts.append('
Aspect-specific metadata attention
')
+ parts.append(_render_meta_matrix_html(np.asarray(meta_by_aspect), token_names))
+ parts.append('