Apache OpenNLP
C-Rank Grade: S (Elite) - 69/100
External PR Merge Rate: 68%
Response Time: -
First Timer Success: 86%
apache/opennlp has a recorded first-timer success rate of 85.7%. Repositories ranked S typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in apache/opennlp respond to incoming external pull requests in approximately 0.0 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.
The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 69.4 places apache/opennlp in the S tier.
The external contributor pull request merge rate for apache/opennlp is 67.8%, based on public PR activity from non-core contributors.
apache/opennlp currently has 2 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".
Strict review standards in apache/opennlp. Ensure PR scope matches issue requirements closely before requesting review.
Average Response Latency
Tracks hours until a maintainer leaves a review, comment, or PR response.
External Acceptance Rate
Percentage of community pull requests successfully merged into main.
First PR Conversion
Rate at which developers submitting their first repository PR succeed.
Show contributors that your repository actively reviews and merges external pull requests.
[](https://getmerged.abhishekco.de/apache/opennlp?utm_source=github&utm_medium=badge)
Historical health & responsiveness evolution
External PR acceptance
First PR success rate
50% receive response in
90% receive response in
Maintainer review activity heatmap & prime window prediction
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Detected: UTC
Maintainers are most responsive around 05:00 UTC (05:00 UTC in your timezone). Recommended submission window is Tuesday - Thursday from 05:00 to 09:00 UTC (05:00 - 09:00 UTC local).
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~16 hours (85% approval). Large PRs (>500 lines) take ~115 hours (30% approval). Keep your diff compact for rapid review.
The spellcheck loaders and model types (FrequencyDictionaryLoader, SymSpellModel, SymSpellModels, SymSpellModelResolver, SuggestItem, SymSpell, SymSpellConfig) reject null arguments with Objects.requireNonNull, so callers get NullPointerException, while the spellcheck streams and normalizer already throw IllegalArgumentException. The public boundaries should use ArgumentChecks.requireNonNullArg and document @throws IllegalArgumentException, so the module validates one way. The exception type change belongs in the 3.0.0 release notes.
AbstractDL.sessionOptions adds the CUDA execution provider before any OrtEnvironment exists. Loading the provider library needs ONNX Runtime's default logger, which only exists once an environment does. The first GPU request in a fresh JVM fails with "Attempt to use DefaultLogger but none has been registered". This affects NameFinderDL, DocumentCategorizerDL and SentenceVectorsDL. To reproduce Use opennlp-dl-gpu, and make a GPU request (InferenceOptions.setGpu(true)) the first ONNX call in the JVM. Fix Create the OrtEnvironment before adding the CUDA provider. A test runs the first CUDA request in a child JVM. The opennlp-dl-gpu test classpath no longer carries the CPU onnxruntime next to onnxruntime_gpu. Branch with a fix and tests: https://github.com/apache/opennlp/tree/fix/onnx-cuda-cold-start
Summary HunspellStemmer in opennlp-runtime has a package-private analyze(CharSequence) that returns each reading as one space-separated Hunspell field string, for example st:work fl:E fl:S or, for a compound, pa:river st:river po:noun pa:boats st:boat po:noun is:plural. It was kept out of the public API in #1270 so that the string layout does not become a frozen contract with 3.0.0. Applications that need more than the stem have no way to get the part of speech, the inflection fields, or the compound parts. The response string is just a string and clients need to parse it - that can be error prone for the client and it should be strongly typed. Proposal Expose analyses as Java objects instead of formatted text: public record HunspellAnalysis(String stem, List<HunspellAnalysis> parts, List<HunspellField> fields) { /** The analysis in Hunspell's field layout, for comparison with the native output. */ public String toHunspellString(); } public record HunspellField(String tag, String
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When evaluating whether to contribute to apache/opennlp, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.
Currently, maintainers of apache/opennlp acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 67.8% were successfully merged into the primary branch.
apache/opennlp has a recorded first-timer success rate of 85.7%. Repositories ranked Elite typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~-. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 69.4 places apache/opennlp in the Elite tier.
The external pull request merge rate is 67.8%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
Yes, apache/opennlp currently has 2 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.
All metrics displayed for apache/opennlp are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.