What is "entity extraction" in Reviato?

It identifies named entities mentioned in review text, people, places, and products or amenities, so you can see what specific things guests keep referencing.

What kinds of entities does Reviato identify?

People (like a staff name mentioned in a review), places (cities, landmarks, transit), and products/amenities (like air conditioning or an espresso machine).

Does entity extraction verify identities or confirm who someone is?

No. It only extracts names and references written in review text; it's not identity verification.

Does Reviato enrich or profile customers using extracted entities?

No. There is no PII enrichment or customer profiling claim here, just extraction from the review itself.

How should I treat staff-name mentions?

As feedback context, not as an HR scoreboard. Use it to understand what guests notice and where service moments stand out.

Can entities be wrong or ambiguous?

Yes. Misspellings, nicknames, and short reviews can produce messy entities. Use them as a pointer, then open the original review.

What's the fastest way to act on an entity trend?

Click into the entity, filter to a recent time window, and read the reviews that mention it to see the common thread.

How does this work with search and filtering?

Entities give you a "what to search for" list. Then you use search and filters to isolate the right platform, location, rating range, and time period.

Does entity extraction create tasks or route issues to departments?

No. It is not ticketing or automated remediation, just structured insight from text.

Features

Entity extraction from reviews (people, places, products)

Identify named entities mentioned in reviews, people, places, and products or amenities, so you can spot repeated mentions and investigate faster.

How to use this page

Use this page as a practical reference, then apply the ideas to your own operation and constraints.

Focus on one actionable change at a time and measure outcomes before moving to the next change.

Key Highlights

People mentions: Spot staff names guests choose to highlight. Understand what service moments stand out.
Place mentions: Catch location expectations, what "central" or "close to transit" actually meant to guests.
Products & amenities: Track repeated operational issues, air conditioning, wifi, shower pressure, across reviews.

Caution

Entity extraction is for insights, not staff performance scoring.

What entity extraction identifies

People

Names guests mention in reviews. Useful context for understanding what service moments stand out.

Places

Cities, landmarks, transit mentions. Often reveal expectation gaps about location and convenience.

Products/amenities

Air conditioning, wifi, espresso machine. Where you catch repeat operational issues.

Operational uses

Repeated mentions of a room/amenity

If "air conditioning" shows up again and again, quickly answer if it's all locations, one floor, or one unit type.

Location/place mentions tied to expectations

When guests mention "airport" or "metro" negatively, it's often an expectation-setting fix, not a branding debate.

Staff-name mentions (insight, not HR tooling)

Use for coaching moments and training opportunities. Not for ranking people.

Where this helps

Amenity issues

Track repeated mentions of air conditioning, wifi, or shower pressure.

Location expectations

Spot mismatched expectations around transit or neighborhood distance.

Staff mentions

Use names as context for coaching, not ranking.

Tired of vague feedback?

Start tracking the specific things guests name.

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