Manually annotated corpora

Manual corpora are collections of texts containing manually validated or manually assigned linguistic information, such as morphosyntactic tags, lemmas, syntactic parses, named entities etc. These corpora can be used to train new language annotation tools as well as to test the accuracy of existing annotation tools.

Corpus Gesproken Nederlands

The Spoken Dutch Corpus comprises a large number of samples of (recorded) spoken text (appr. 9 million words). The entire corpus has been transcribed orthographically, while the transcripts have been linked to the speech files. The orthographic transcription was used as the starting point for the lemmatization and part-of-speech tagging of the corpus. For a selection of one million words, a (verified) broad phonetic transcription has been produced, while for this part of the corpus also the alignment of the transcripts and the speech files has been verified at the word level. In addition, a selection of one million words has been annotated syntactically. Finally, for a more modest part of the corpus, approximately 250,000 words, a prosodic annotation is available.

• Corpus page

Eindhoven Corpus

The Eindhoven corpus (VU version) is a collection of Dutch written and transcribed spoken texts from the period from 1960 to 1976. The corpus contains approximately 768,000 tokens. It is the first collection of Dutch written and (transcribed) spoken texts.

• version 2.0.1 (2014)
• 3 MB
• Download link

Lassy Small

The Lassy Small Corpus is a corpus of approximately 1 million words with manually verified syntactical annotations. The lemmas and POS-tags were generated with Tadpole (now Frog) and the syntactical depency structures were generated with Alpino. The lemmas, POS-tags and syntactic tree structures were manually verified and corrected.

• Version 7.0
• Download
• Online treebank search

SoNaR Small Corpus

The SoNaR Small Corpus Commercial contains approx. 825.000 words which were manually semantically annotated. This is a subset of the much larger (approx. 500 million word) SoNaR corpus.

• Various versions of the SoNaR Corpus
• Download page

ACTER: Annotated Corpora for Term Extraction Research

The ACTER (Annotated Corpora for Term Extraction Research) is an annotated dataset for term extraction. Terms and Named Entities have been manually annotated in specialised comparable corpora covering 3 languages (English, French, and Dutch), and 4 domains (corruption, dressage, heart failure, and wind energy).

• CLARIN page
• Github page
• Rigouts Terryn, Ayla, 2019, ACTER (Annotated Corpora for Term Extraction Research) v1.3, Eurac Research CLARIN Centre

Dutch Archaeology NER Training Dataset

A manually annotated NER dataset, consisting of Dutch archaeological excavation reports. The following entity types are labelled: Artefacts, Time periods, Materials, Places (geographical locations), Archaeological contexts and Species. The dataset is provided in the BIO format, with each token on 1 line and empty lines denoting sentence boundaries. On each line you can find the token, PoS tag, morphological segmentation and finally the label, separated by spaces. The PoS tag and morphological segmentation are assigned by Frog.

• Version 1.0 (2019)
• Download page

StylesNMT

This data repository contains an English-Dutch machine translation (MT) of the detective novel "The Mysterious Affair at Styles" by Agatha Christie. The translation was generated in May 2019 by Google's neural MT system. The complete novel (5,276 sentence pairs) has been manually annotated with translation errors using an adapted version of the SCATE MT error taxonomy (Tezcan et al. 2017).

• Download page
• Tezcan, A., Hoste, V., & Macken, L. (2017). SCATE taxonomy and corpus of machine translation errors. In G. C. Pastor & I. Durán-Muñoz (Eds.), Trends in E-tools and resources for translators and interpreters (Vol. 45, pp. 219–244). Brill | Rodopi.

Pilot Annotation Corpus PLATOS NL-EN

This annotated corpus consists of 100 user-comments sourced on Facebook in the Summer of 2020, on the Facebook page of a popular flemish newspaper (Het Laatste Nieuws, https://www.facebook.com/hln.be).This corpus contains both the original comments in Dutch and a parallel English translation (Google Translate output lightly edited for correctness by a native speaker). The annotation covers topic and aspect labelling, stance labelling, argumentativeness detection and claim identification.

• Download link
• Bauwelinck, N., & Lefever, E. (2020, December). Annotating Topics, Stance, Argumentativeness and Claims in Dutch Social Media Comments: A Pilot Study. In Proceedings of the 7th Workshop on Argument Mining (pp. 8-18).

EventDNA

The EventDNA corpus is a Dutch-language corpus comprising 1,773 news documents in which news events, entities, IPTC Media Topic codes and coreference links have been manually annotated.

• EventDNA: Annotation Guidelines forEntities and Events in Dutch News Texts (v1.0) Camiel Colruyt, Orphée De Clercq and Véronique Hoste
• Code for both the event extraction experiments and IAA study
• Info page (a.o. concerning access to the corpus data)

EmotioNL

The EmotioNL Corpus is an emotion-annotated corpus of Dutch texts. It consists of 1,000 Dutch tweets and 1,000 captions from reality TV-shows, annotated with the categories anger, fear, joy, love, sadness and neutral, and scores (real-valued, between 0 and 1) for the emotional dimensions valence, arousal and dominance.

• De Bruyne, L., De Clercq, O., & Hoste, V. (2021). Prospects for Dutch emotion detection: Insights from the new EmotioNL dataset. Computational Linguistics in the Netherlands Journal, 11, 231-255.
• Info page (a.o. concerning access to the corpus data)

EmoWOZ-CS EN-NL

The EmoWOZ corpus is a text-based conversational corpus in the domain of customer service, collected through the Wizard of Oz technique. In our Wizard of Oz experiment, participants believed to be interacting with different versions of an autonomous chatbot (called Chatty), while the system was in reality fully controlled by a human operator (henceforth: wizard). Each dialogue was grounded in an event description associated with a begin sentiment (neutral or negative), and wizards were instructed to navigate the conversation to a predefined end sentiment (positive, neutral or negative). Each participant had 12 conversations which were subsequently annotated for emotions with emotion categories and dimensional valence-arousal-dominance scores. In total, the corpus contains 2,148 text-based dialogues between 179 participants and wizards. While the original version of the corpus was collected in Dutch (NL), a translated version to English (EN) is also made available.

• Project page
• Labat, S., Ackaert, N., Demeester, T., & Hoste, V. (2022). Variation in the Expression and Annotation of Emotions: a Wizard of Oz Pilot Study. In G. Abercrombie, V. Basile, S. Tonelli, V. Rieser, & A. Uma (Eds.), Proceedings of the 1st Workshop on Perspectivist Approaches to NLP @LREC2022 (pp. 66–72). Marseille, France: European Language Resources Association (ELRA)

EmoTwiCS

EmoTwiCS is a corpus of 9,489 Dutch customer service dialogues that were scraped from Twitter.

Labat, S., Demeester, T., & Hoste, V. (2023). EmoTwiCS : a corpus for modelling emotion trajectories in Dutch customer service dialogues on Twitter. Labat, S., Hadifar, A., Demeester, T., & Hoste, V. (2022). An emotional journey : detecting emotion trajectories in Dutch customer service dialogues Request access

Crowll corpora

Manually annotated corpora for teaching and learning purposes of Brazilian Portuguese, Dutch, Estonian, and Slovene. Sentences are annotated with “problematic” or “non-problematic” labels, from the point of usage for pedagogical purposes. Sentences labelled as problematic also have annotations defining the category of the problem (offensive, vulgar, sensitive content, grammar and/or spelling problems, incomprehensible and/or lack of context). Each corpus consists of 10.000 sentences, which were annotated by language experts.

• Dataset Website
• Project website