Photo credits

All photographs on Parallel Text are in the public domain or released under the Creative Commons CC0 dedication, and were found on Wikimedia Commons. Several are works of the US federal government (National Archives, US Army, National Park Service) or come from the Library of Congress. Each image was resized and cropped to a 3:2 format and converted to WebP; no other changes were made. No image, logo or graphic from the former website on this domain has been used.

Photos illustrate a topic. People and places shown have no connection with Parallel Text, and their appearance does not imply any endorsement.

Photos by page

• Home page (top): Museum visitors leaning on a rail to look at the Rosetta Stone, a dark inscribed slab displayed at an angle. Photo: Rick Dikeman, Rosetta-stone-display-in-1985.jpg (Wikimedia Commons), CC0.
• Bias in NLP: Where It Comes From, How It Is Measured and What Helps: Two women programmers set up the wiring panels of the room-sized ENIAC computer in a black-and-white photograph. Photo: Unidentified U.S. Army photographer, Reprogramming ENIAC.png (Wikimedia Commons), Public domain.
• Dataset Licences for NLP: Creative Commons, Open Data Commons and the EU Rules: Rows upon rows of stacked boxes of punched record cards filling a large warehouse floor. Photo: US National Archives, IBM card storage.NARA.jpg (Wikimedia Commons), Public domain.
• Datasheets, Data Statements and Model Cards: Documenting NLP Data and Models: An old bound laboratory logbook lying open on a desk, its handwritten pages yellowed and stained. Photo: Daderot, Lab book - Lawrence Berkeley National Laboratory - DSC08822.JPG (Wikimedia Commons), Public domain.
• Language Technology in Europe: 24 Official Languages and the Digital Divide: A street at the entrance of a small town with half-timbered houses, a banner over the road and a stone gate bearing a bilingual sign. Photo: Ulamm, S-Jean-Pied-de-P Donibane.png (Wikimedia Commons), Public domain.
• How NLP Models Are Evaluated: Benchmarks, Metrics and Their Blind Spots: A yellow tape measure marked in feet and centimetres lying on a wooden floor next to two copper coins. Photo: Stilfehler, Measuring Tape Inch+CM.jpg (Wikimedia Commons), Public domain.
• GDPR and Text Data: Personal Data in NLP Corpora and Models: A rusty metal hasp and padlock fastening a weathered red wooden door. Photo: Estormiz, Padlock Valimokatu Oulu 20250307 01.jpg (Wikimedia Commons), CC0.
• How Tokenization Works: Words, Subwords and Bytes in NLP: Close-up black-and-white photograph of round typewriter keys arranged in staggered rows. Photo: Ralph Steiner (Clarence H. White School of Photography), Typewriter keys LCCN2004666344.jpg (Wikimedia Commons), Public domain.
• Low-Resource Languages in NLP: What "Low-Resource" Means and What Works: A wooden printer's type case full of metal type pieces for the Cherokee syllabary, scattered in its compartments. Photo: National Trails Office (US National Park Service), Historic Cherokee printing press letters at New Echota in Gordon County, Georgia (9fb7abb0-05d3-415b-a671-839f2fd5505a).JPG (Wikimedia Commons), Public domain.
• Machine Translation Evaluation: BLEU, chrF, COMET and Human Judgement: Two men wearing headphones sit at a desk with microphones and an amplifier, working as interpreters in a black-and-white photograph. Photo: Unknown author, German War Crimes Trials. Nuernberg & Dachau - NARA - 292602 (cropped).jpg (Wikimedia Commons), Public domain.
• Machine Translation for Tenants Moving Abroad: What Works and What to Check: A row of three-storey brick apartment houses with bay windows and small rental signs in the windows, in an old black-and-white photograph. Photo: Unknown author, Residential buildings with "For Rent" signs on an unidentified street.jpg (Wikimedia Commons), Public domain.
• Multilingual Lexical Knowledge Bases: WordNets, BabelNet and Wikidata Explained: The domed main reading room of the Library of Congress, with concentric rings of desks around a central circulation desk. Photo: Carol M. Highsmith, LOC Main Reading Room Highsmith.jpg (Wikimedia Commons), Public domain.
• Parallel Corpora: How Translated Text Trains Machine Translation: A printed notice taped to a glass door announcing holiday closing dates in English, with a greeting in Basque below. Photo: Terfili, Basque notice in Boise, Idaho.JPG (Wikimedia Commons), Public domain.
• Reproducibility in NLP: Why Results Fail to Repeat and How to Fix It: Two handwritten pages of a nineteenth-century laboratory notebook with a small sketch of apparatus and dated entries. Photo: Alexander Graham Bell, AGBell Notebook.jpg (Wikimedia Commons), Public domain.
• Web-Scraped Corpora: Copyright, Consent and Opt-Outs in NLP: A server rack packed with stacked machines, blue status displays and bundles of white network cables. Photo: Derrick Coetzee, Rear of rack at NERSC data center - closeup.jpg (Wikimedia Commons), CC0.
• What Makes a Language Model "Open"? Weights, Data, Code and Licences: A technician in a checked shirt crouches with a laptop in front of an open server rack in a data centre. Photo: Derrick Coetzee, Technician with laptop working on server rack at NERSC.jpg (Wikimedia Commons), CC0.
• Word Sense Disambiguation: How Machines Decide What a Word Means: A metal drawer full of index cards from a card catalogue, resting on a wooden table. Photo: Michael Holley, Copyright Card Catalog Drawer.jpg (Wikimedia Commons), Public domain.

Typefaces

Crimson Pro (Jacques Le Bailly) and Space Grotesk (Florian Karsten), both under the SIL Open Font License 1.1, served from this site.