Merge remote-tracking branch 'origin/main'

Author: Mocretion

docs/index.md

@@ -197,6 +197,8 @@ the number of most-recent frames to include. Built on `where_am_i`.
 
 ### Examples
 
+A complete example component can be found [here](https://github.com/texttechnologylab/DockerUnifiedUIMAInterface/tree/main/test_containers/python_logging/letter_counter).
+
 ```python
 # Plain info
 log_info("loaded model")
@@ -295,3 +297,48 @@ Everything below is importable from the top-level `duui_logging` package.
 | `DUUICollectHandler` | class | the `logging.Handler` `install` attaches |
 | `ErrorLevel` | enum | the six level names |
 | `LogRecord` | model | the wire format shared with Java |
+
+
+# Cite
+If you want to use the project please quote this as follows:
+
+Alexander Leonhardt, Giuseppe Abrami, Daniel Baumartz and Alexander Mehler. (2023). "Unlocking the Heterogeneous Landscape of Big Data NLP with DUUI." Findings of the Association for Computational Linguistics: EMNLP 2023, 385–399. [[LINK](https://aclanthology.org/2023.findings-emnlp.29)] [[PDF](https://aclanthology.org/2023.findings-emnlp.29.pdf)]
+
+Daniel Bundan, Giuseppe Abrami (2026). "DUUI Logging". [[LINK](https://github.com/texttechnologylab/DUUIlogger)]
+
+## BibTeX
+```
+@inproceedings{Leonhardt:et:al:2023,
+  title     = {Unlocking the Heterogeneous Landscape of Big Data {NLP} with {DUUI}},
+  author    = {Leonhardt, Alexander and Abrami, Giuseppe and Baumartz, Daniel and Mehler, Alexander},
+  editor    = {Bouamor, Houda and Pino, Juan and Bali, Kalika},
+  booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2023},
+  year      = {2023},
+  address   = {Singapore},
+  publisher = {Association for Computational Linguistics},
+  url       = {https://aclanthology.org/2023.findings-emnlp.29},
+  pages     = {385--399},
+  pdf       = {https://aclanthology.org/2023.findings-emnlp.29.pdf},
+  abstract  = {Automatic analysis of large corpora is a complex task, especially
+               in terms of time efficiency. This complexity is increased by the
+               fact that flexible, extensible text analysis requires the continuous
+               integration of ever new tools. Since there are no adequate frameworks
+               for these purposes in the field of NLP, and especially in the
+               context of UIMA, that are not outdated or unusable for security
+               reasons, we present a new approach to address the latter task:
+               Docker Unified UIMA Interface (DUUI), a scalable, flexible, lightweight,
+               and feature-rich framework for automatic distributed analysis
+               of text corpora that leverages Big Data experience and virtualization
+               with Docker. We evaluate DUUI{'}s communication approach against
+               a state-of-the-art approach and demonstrate its outstanding behavior
+               in terms of time efficiency, enabling the analysis of big text
+               data.}
+}
+
+@misc{Bundan_2026,
+  title     = {DUUI Logging},
+  author    = {Bundan, Daniel and Abrami, Giuseppe},
+  year      = {2026},
+  month     = {Aug},
+  url       = {https://github.com/texttechnologylab/DUUIlogger}
+}