This prototype uses state-of-the-art artificial intelligence, including a vision-language model (VLM) capable of reading handwritten documents as well as typed and printed text, to create searchable transcriptions of digitized materials in the Hunt Institute Archives. This makes it possible to search the textual contents of individual pages, including material that may not be described in the archival catalog.
Use Keyword search for specific words, names, dates, scientific names, or phrases. Try Semantic search (experimental) to describe a topic, question, or kind of material when you do not know the exact wording used in the documents.
The transcriptions are generated automatically from page images and may contain errors, especially with difficult handwriting, unusual names, multiple languages, image-quality problems, or complex layouts. They are intended primarily as a discovery aid rather than authoritative transcriptions.
Each result provides the generated transcription and links to the original digitized material and associated archival description so that readings can be checked against the source. The transcription workflow uses AI models run locally by the Hunt Institute.
Keyword search is the default and matches the wording in the
transcriptions. Results contain all your terms. Use quotes for an exact
phrase. Substring matching is supported, so aceae can find plant-family
names ending in -aceae.
Semantic search (experimental) is useful when you know what kind of material you are looking for but do not know the words used in the documents. It ranks transcribed passages by similarity of meaning, so relevant results may not contain the exact words in your query.
Semantic queries can be broad research topics, descriptions of activities or relationships, or natural-language questions. For example:
plant collecting and fieldwork in South America
medicinal, culinary, or other traditional uses of plants
chromosomes and plant classification
early herbals and botanical illustrations
botanical institutions exchanging plants, seeds, and specimens
microscopy and photomicrography in botanical research
How did botanists and gardeners introduce plants from one region to another?
grafting, budding, and propagation of tropical fruit crops
Semantic search is not a chatbot: a question is used as a search query, and the system returns archival passages that appear conceptually related to it rather than generating an answer or summary. Short descriptions and ordinary research questions generally work better than lists of disconnected keywords. Quotation marks have no special meaning in Semantic mode. Cross-language matching may work in some cases, but it should not be treated as translation.
Keyword and Semantic search are complementary. Keyword search lets you require particular wording; Semantic search can surface differently worded passages about the same subject. Depending on the research question, trying both can reveal different useful material.
Open a result: use the prominent page-and-transcription link to see the metadata, PDF, and full transcription. Keyword-search terms are highlighted in the transcription.
Archives Collections Database (ArchivesSpace): the Collection, Item/Folder, and Digital Object links open the corresponding archival records. Collection-level dates describe the collection as a whole, not necessarily the specific item or page.
If a PDF does not load: on the detail page, use the Digital Object link, click “Go to file” in ArchivesSpace, and navigate to the page number shown here.
Valeriana officinalis Valerian root Cichorium intybus Chicory Matricaria chamomilla Chamomile flowers Symphytum officinale Comfrey Rosa canina Rose Hips Leonurus cardiaca Mugwort Verbascum thapsus Mullein