leoworks/korean-review-classifier
leoworks--korean-review-classifierDestructive
This tool calls the Actor "leoworks/korean-review-classifier" and retrieves its output results. Actor description: Classify Korean customer reviews — Coupang reviews (쿠팡 리뷰), Olive Young reviews, Naver Shopping and Naver Place reviews — into complaint types, sentiment and purchase motive with probabilities. Korean review sentiment analysis for any review scraper's dataset — no prompts, no LLM key.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| texts | No | Paste review texts directly (one per line). Use this OR “Reviews dataset”. Example values: ["배송이 일주일이나 걸렸고 박스가 다 찢어져서 왔어요.","항상 쓰던 거라 이번에도 재구매했어요. 할인할 때 사니 좋네요!"] | |
| idFields | No | Fields copied unchanged from each input item to the output so you can join results back (e.g. reviewId, productId). Leave empty to auto-pick reviewId/id/url. | |
| maxItems | No | Classify at most this many reviews (0 = all). | |
| waitSecs | No | Max seconds (0–45, default 30) to cap the wait for the Actor run to reach terminal state. For long-running Actors the response returns at the cap with the current run status; follow `nextStep` to poll via get-actor-run. Set to 0 to fire-and-forget. | |
| datasetId | No | An Apify dataset containing reviews — for example the output of a Coupang, Naver Shopping, Naver Place or Olive Young review scraper. Use this OR “Review texts”. | |
| textField | No | Field holding the review text. Leave empty to auto-detect (content, text, review, body, reviewText, …). | |
| outputMode | No | Minimal mode returns only label keys — smaller and easier to aggregate. Example values: "full" | full |
| healthCheck | No | Internal: fail the run when results look degraded (used by the developer's scheduled checks). | |
| customLabels | No | Up to 10 extra yes/no labels (each up to 200 characters) written in plain language (English or Korean), e.g. “mentions the smell”, “배송 기사 불친절 언급”. Each gets a probability. | |
| maxConcurrency | No | Reviews classified in parallel. Example values: 10 | |
| extraTextFields | No | Fields to prepend to the text (up to 5), e.g. `title` for Coupang review headlines. Leave empty if unsure. | |
| summaryGroupField | No | Field in your dataset that identifies the product (e.g. `productId`, `productName`, `placeId`). The run then saves a REPORT record with, per product: complaint rate and complaint mix, sentiment shares, purchase motives, average rating and 3 example complaints. Leave empty to detect it automatically (overall summary only if none is found). No extra charge. | |
| complaintThreshold | No | Minimum probability (0–1) for a complaint type or custom label to be reported. Raise it for fewer, surer labels. Example values: 0.5 |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| tip | No | Advisory guidance RAG Web Browser wrote to its key-value store under the reserved "TIP" key | |
| runId | Yes | Actor run ID | |
| stats | No | Run statistics | |
| status | Yes | Run status: READY | RUNNING | TIMING-OUT | TIMED-OUT | ABORTING | ABORTED | SUCCEEDED | FAILED | |
| actorId | Yes | Stable Apify Actor ID from the run record | |
| summary | Yes | Past-tense summary of the run state | |
| exitCode | No | Actor process exit code; populated for terminal states (especially FAILED) | |
| nextStep | Yes | One primary follow-up action with identifiers interpolated | |
| storages | Yes | Dataset and key-value store metadata, keyed by alias. "default" is always the primary entry. | |
| actorName | No | "username/actor-name" | |
| startedAt | No | ISO timestamp when the run started | |
| finishedAt | No | ISO timestamp when the run finished (terminal states only) | |
| statusMessage | No | Pass-through from Apify run.statusMessage | |
| apifyConsoleUrl | No | Personalized Apify Console link to the run; present only for Console sessions |