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Creamy appetizers--taramasalata, eggplant salad, and Greek yogurt (with cuccumber, dill, and garlic) taste excellent when on warm pitas.
Predict(StringSignature(text -> aspects
instructions='These guidelines detail Aspect Based Sentiment Analysis Annotation for restaurant and laptop customer reviews. The aim is to determine aspect terms and their sentiment polarities within sentences. Aspect terms are words or phrases describing the specific attributes of the target entity. Sentiment polarity can be positive, negative, or neutral. For aspect terms, annotators should mark nominal phrases explicitly mentioning aspects and verbs...
Prediction(
aspects=Aspects(aspects=[Aspect(term='appetizers', polarity='positive'), Aspect(term='taramasalata', polarity='positive'), Aspect(term='eggplant salad', polarity='positive'), Aspect(term='Greek yogurt', polarity='positive'), Aspect(term='pitas', polarity='positive')])
)
1,750
$0.0009
15ms
13.9kB
Although the restaurant itself is nice, I prefer not to go for the food.
Predict(StringSignature(text -> aspects
instructions='These guidelines detail Aspect Based Sentiment Analysis Annotation for restaurant and laptop customer reviews. The aim is to determine aspect terms and their sentiment polarities within sentences. Aspect terms are words or phrases describing the specific attributes of the target entity. Sentiment polarity can be positive, negative, or neutral. For aspect terms, annotators should mark nominal phrases explicitly mentioning aspects and verbs...
Prediction(
aspects=Aspects(aspects=[Aspect(term='restaurant', polarity='neutral'), Aspect(term='food', polarity='negative')])
)
1,691
$0.0009
24ms
13.3kB
I have never in my life sent back food before, but I simply had to, and the waiter argued with me over this.
Predict(StringSignature(text -> aspects
instructions='These guidelines detail Aspect Based Sentiment Analysis Annotation for restaurant and laptop customer reviews. The aim is to determine aspect terms and their sentiment polarities within sentences. Aspect terms are words or phrases describing the specific attributes of the target entity. Sentiment polarity can be positive, negative, or neutral. For aspect terms, annotators should mark nominal phrases explicitly mentioning aspects and verbs...
Prediction(
aspects=Aspects(aspects=[Aspect(term='food', polarity='negative'), Aspect(term='waiter', polarity='negative')])
)
1,702
$0.0009
26ms
13.4kB
Owner is pleasant and entertaining.
Predict(StringSignature(text -> aspects
instructions='These guidelines detail Aspect Based Sentiment Analysis Annotation for restaurant and laptop customer reviews. The aim is to determine aspect terms and their sentiment polarities within sentences. Aspect terms are words or phrases describing the specific attributes of the target entity. Sentiment polarity can be positive, negative, or neutral. For aspect terms, annotators should mark nominal phrases explicitly mentioning aspects and verbs...
Prediction(
aspects=Aspects(aspects=[Aspect(term='Owner', polarity='positive')])
)
1,672
$0.0009
32ms
13.0kB
Anyway, the owner was fake.
Predict(StringSignature(text -> aspects
instructions='These guidelines detail Aspect Based Sentiment Analysis Annotation for restaurant and laptop customer reviews. The aim is to determine aspect terms and their sentiment polarities within sentences. Aspect terms are words or phrases describing the specific attributes of the target entity. Sentiment polarity can be positive, negative, or neutral. For aspect terms, annotators should mark nominal phrases explicitly mentioning aspects and verbs...
Prediction(
aspects=Aspects(aspects=[Aspect(term='owner', polarity='negative')])
)
1,673
$0.0009
30ms
13.0kB
Its good to go there for drinks if you don't want to get drunk because you'll be lucky if you can get one drink an hour the service is so bad.
Predict(StringSignature(text -> aspects
instructions='These guidelines detail Aspect Based Sentiment Analysis Annotation for restaurant and laptop customer reviews. The aim is to determine aspect terms and their sentiment polarities within sentences. Aspect terms are words or phrases describing the specific attributes of the target entity. Sentiment polarity can be positive, negative, or neutral. For aspect terms, annotators should mark nominal phrases explicitly mentioning aspects and verbs...
Prediction(
aspects=Aspects(aspects=[Aspect(term='drinks', polarity='positive'), Aspect(term='service', polarity='negative')])
)
1,710
$0.0009
26ms
13.5kB
I always find myself sitting next to someone in the theatre industry- interesting to hear ideas hashed out while having a quick bite to eat.
Predict(StringSignature(text -> aspects
instructions='These guidelines detail Aspect Based Sentiment Analysis Annotation for restaurant and laptop customer reviews. The aim is to determine aspect terms and their sentiment polarities within sentences. Aspect terms are words or phrases describing the specific attributes of the target entity. Sentiment polarity can be positive, negative, or neutral. For aspect terms, annotators should mark nominal phrases explicitly mentioning aspects and verbs...
Prediction(
aspects=Aspects(aspects=[])
)
1,684
$0.0009
30ms
13.2kB
Sweet Irish bartender is always happy and able to bring a smile to my friends a my face.
Predict(StringSignature(text -> aspects
instructions='These guidelines detail Aspect Based Sentiment Analysis Annotation for restaurant and laptop customer reviews. The aim is to determine aspect terms and their sentiment polarities within sentences. Aspect terms are words or phrases describing the specific attributes of the target entity. Sentiment polarity can be positive, negative, or neutral. For aspect terms, annotators should mark nominal phrases explicitly mentioning aspects and verbs...
Prediction(
aspects=Aspects(aspects=[Aspect(term='bartender', polarity='positive')])
)
1,686
$0.0009
46ms
13.2kB
It gets very crowded so I would suggest that you get their early.
Predict(StringSignature(text -> aspects
instructions='These guidelines detail Aspect Based Sentiment Analysis Annotation for restaurant and laptop customer reviews. The aim is to determine aspect terms and their sentiment polarities within sentences. Aspect terms are words or phrases describing the specific attributes of the target entity. Sentiment polarity can be positive, negative, or neutral. For aspect terms, annotators should mark nominal phrases explicitly mentioning aspects and verbs...
Prediction(
aspects=Aspects(aspects=[])
)
1,671
$0.0009
48ms
13.0kB
Weekends can get crowded, but still highly recommended.
Predict(StringSignature(text -> aspects
instructions='These guidelines detail Aspect Based Sentiment Analysis Annotation for restaurant and laptop customer reviews. The aim is to determine aspect terms and their sentiment polarities within sentences. Aspect terms are words or phrases describing the specific attributes of the target entity. Sentiment polarity can be positive, negative, or neutral. For aspect terms, annotators should mark nominal phrases explicitly mentioning aspects and verbs...
Prediction(
aspects=Aspects(aspects=[Aspect(term='Weekends', polarity='neutral')])
)
1,678
$0.0009
50ms
13.1kB
I stopped by for some brunch today and had the vegan cranberry pancakes and some rice milk.
Predict(StringSignature(text -> aspects
instructions='These guidelines detail Aspect Based Sentiment Analysis Annotation for restaurant and laptop customer reviews. The aim is to determine aspect terms and their sentiment polarities within sentences. Aspect terms are words or phrases describing the specific attributes of the target entity. Sentiment polarity can be positive, negative, or neutral. For aspect terms, annotators should mark nominal phrases explicitly mentioning aspects and verbs...
Prediction(
aspects=Aspects(aspects=[Aspect(term='brunch', polarity='positive'), Aspect(term='vegan cranberry pancakes', polarity='positive'), Aspect(term='rice milk', polarity='positive')])
)
1,709
$0.0009
31ms
13.5kB
I asked repeatedly what the status of the meal was and was pretty much grunted at by the unbelievably rude waiter.
Predict(StringSignature(text -> aspects
instructions='These guidelines detail Aspect Based Sentiment Analysis Annotation for restaurant and laptop customer reviews. The aim is to determine aspect terms and their sentiment polarities within sentences. Aspect terms are words or phrases describing the specific attributes of the target entity. Sentiment polarity can be positive, negative, or neutral. For aspect terms, annotators should mark nominal phrases explicitly mentioning aspects and verbs...
Prediction(
aspects=Aspects(aspects=[Aspect(term='status of the meal', polarity='neutral'), Aspect(term='waiter', polarity='negative')])
)
1,703
$0.0009
56ms
13.4kB
I just had my first visit to this place and can't wait to go back and slowly work my way through the menu.
Predict(StringSignature(text -> aspects
instructions='These guidelines detail Aspect Based Sentiment Analysis Annotation for restaurant and laptop customer reviews. The aim is to determine aspect terms and their sentiment polarities within sentences. Aspect terms are words or phrases describing the specific attributes of the target entity. Sentiment polarity can be positive, negative, or neutral. For aspect terms, annotators should mark nominal phrases explicitly mentioning aspects and verbs...
Prediction(
aspects=Aspects(aspects=[Aspect(term='place', polarity='neutral'), Aspect(term='menu', polarity='neutral')])
)
1,700
$0.0009
31ms
13.3kB
I'm looking forward to going back soon and eventually trying most everything on the menu!
Predict(StringSignature(text -> aspects
instructions='These guidelines detail Aspect Based Sentiment Analysis Annotation for restaurant and laptop customer reviews. The aim is to determine aspect terms and their sentiment polarities within sentences. Aspect terms are words or phrases describing the specific attributes of the target entity. Sentiment polarity can be positive, negative, or neutral. For aspect terms, annotators should mark nominal phrases explicitly mentioning aspects and verbs...
Prediction(
aspects=Aspects(aspects=[Aspect(term='menu', polarity='neutral')])
)
1,683
$0.0009
60ms
13.2kB
i have eaten here on a different occasion - the food is mediocre for the prices.
Predict(StringSignature(text -> aspects
instructions='These guidelines detail Aspect Based Sentiment Analysis Annotation for restaurant and laptop customer reviews. The aim is to determine aspect terms and their sentiment polarities within sentences. Aspect terms are words or phrases describing the specific attributes of the target entity. Sentiment polarity can be positive, negative, or neutral. For aspect terms, annotators should mark nominal phrases explicitly mentioning aspects and verbs...
Prediction(
aspects=Aspects(aspects=[Aspect(term='food', polarity='negative'), Aspect(term='prices', polarity='negative')])
)
1,692
$0.0009
26ms
13.3kB
The food was mediocre and the service was severely slow.
Predict(StringSignature(text -> aspects
instructions='These guidelines detail Aspect Based Sentiment Analysis Annotation for restaurant and laptop customer reviews. The aim is to determine aspect terms and their sentiment polarities within sentences. Aspect terms are words or phrases describing the specific attributes of the target entity. Sentiment polarity can be positive, negative, or neutral. For aspect terms, annotators should mark nominal phrases explicitly mentioning aspects and verbs...
Prediction(
aspects=Aspects(aspects=[Aspect(term='food', polarity='negative'), Aspect(term='service', polarity='negative')])
)
1,686
$0.0009
50ms
13.2kB
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