Hunt Institute for Botanical Documentation
A Research Division of Carnegie Mellon University

Hunt Institute Archives Text Discovery Platform

Search a large and growing portion of our online collections, including handwritten documents.
PROTOTYPE

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.

About the AI-generated transcriptions

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.

About Keyword and Semantic search

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:

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.

Current limitations
  • Automated transcriptions can contain missing or incorrect text or unintended repetition. Difficult handwriting, image quality, unusual layouts, and multiple languages can reduce accuracy. Always consult the original page image when an exact reading matters.
  • Semantic search remains experimental. Its rankings are an additional discovery aid, not a complete or definitive set of relevant results, and highly ranked pages can sometimes be only broadly related.
  • This is an active prototype. Search coverage, transcriptions, functionality, and the interface may continue to change as additional archival material is processed and the system is improved.

← Back to results

Page 95 · DO #4531 · 116_Van%20Schaack_Bx6FF19_r

Collection
George B. Van Schaack (1903–1983) papers
Item/Folder
Miscellaneous (1 of 2), 1945–1981
Digital Object
DO #4531, page 95
Collection-level dates
1918–1981
Open PDF at page 95 ↗

Page transcription

Aemilius Macer wrote his De viribus herbarum in 2269 hexameters, presenting
65 medicinal plants and 12 spices. His work, too, is derived from Dioskorides,
Pliny and others. His poem was very popular, there being over a dozen mss
versions known and over a score of printed editions.

The second group of herbals is made up of a remarkable group of three titles,
each appearing in its first edition in the German city of Mainz, the seat of
the first European printing with movable type. Authorship here is much less
definite than in the first group; in fact, these works are always referred to
by their titles. They are:
1484 Herbarius Moguntinus
1485 Gart der Gesundheit
1491 Hortus sanitatis

The first of these is in Latin and was probably printed from a now no longer
existant late mediaeval ms. The second is in German and is an original work
specifically written to make the lore of herbs available to the common man. The
third is again in Latin, ostensibly a true herbal, but according to its author,
who is known, an early renaissance attempt to give an account of the physical
world. All of these works were immediately reprinted in many editions and
translated into several languages. We shall discuss them in more detail in
connection with the slides.

The third group of herbals is headed by the works of two Germans and one
Italian. These are:
Brunfels, O. Herbarum vivae eicones. 1530.
Fuchs, L. De historia stirpium. 1542.
Mattioli, P. A. Di Pedacis Dioscoride Anazarbeo libri cinque della
historia et materia medicinale. 1544.

In general these are much more ambitious books, most of their editions
being physically of large size with nearly life-size drawings from live plants.
The first one is of great importance because it was the earliest to use this type