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 8 · DO #1312 · Archer Vol.2_1_r

Collection
William Andrew Archer (1894–1973) papers
Item/Folder
Volume 2, 1937–1939
Digital Object
DO #1312, page 8
Collection-level dates
1929–1964
Open PDF at page 8 ↗

Page transcription

Percy Train
Lower Rochester, Nev.
Page 3
Medicinal and food uses of some Nevada plants, cont'd.

13. BALSAMORHIZA hirsuta (Key-gah-da-Goop)
Classed as especially "good medicine". First used by the Indians around Bishop, Calif., the word was passed on north and into Nevada around Smith Valley and Walker River. This information then spread to McDermitt and Summit Lake reservations.
The roots is boiled, the resulting solution appearing like a thin yellow soup. Used internally in bad stomach diseases and bladder trouble. (Plant noted in the Martin Creek basin of this range.)

14. LEWISIA rediviva (Ki-neech) Montana bitter root
Used as a food only, in the spring. Roots peeled before cooking.

15. ARTEMESIA tridentata (A sah-wavvy) *not wavy, but to sound like Mohave.
The dead leaves of the sagebrush were gathered by the squaws, ground up to a fine powder, and used as a talcum powder. Indians called it "baby powder."
*Green leaves of the sagebrush were boiled and used as a hot tea drink for colds and cough.

16. SALIX sp. (Gee-see sub-e-wee) (Goe-see means gray, sub-e-wee means the little leaf grey or white willow along stream banks.
Pull off the bark and boil the willow wood as a tea. The Indians claim it just as good a physic as epson salts.

17. RED CURRANT (wild) Poh-on-bis
The wild red currant has two barks. The Indians took off and discarded the outer bark, taking the inner bark dried and scraped and made into a powder. This powder when applied, dried up running sores.

18. SAMBUCUS melanocarpa (Koon-noo-gip) Elderberry.
The roots of the elderberry were mashed to a pulp, and applied as a poultice for caked breast pain in breast, berries were dried and eaten as food.