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 #1049 · 1_Allen_Bx1FF7r

Collection
Paul Hamilton Allen (1911–1963) papers
Item/Folder
Correll, Donovan Stewart (1908–1983), 1950–1959
Digital Object
DO #1049, page 8
Collection-level dates
1937–1963
Open PDF at page 8 ↗

Page transcription

CENTRO NACIONAL DE AGRONOMIA
SANTA TECLA, EL SALVADOR

August 25, 1958

Dr. Donovan S. Correll, Head
Botanical Laboratory
Texas Research Foundation
Renner, Texas

Dear Don:

Your good letter regarding the possibility of securing duplicate specimens from Central America was forwarded to me from Zamorano and has perhaps come at an opportune moment, since I am in the process of trying to organize a small herbarium that I have found here, as a preliminary step in the production of a timber utilization manual for the country. It is already apparent that there are going to be a lot of duplicates, but a great many are unidentified, and without ANY information as to where, when or by whom they were collected. A high percentage of these can be named, and I plan to distribute duplicates to one or two institutions here in the country, who will be willing to take anything known to occur in the country, and no questions asked. Perhaps 40 or 50% have at least locality data, and the name of the collector, and these might be of more interest to you. Let me have your reaction to this, in any case, and I in turn will let you know how many specimens might be available, when I have had a chance to work through the lot, which runs to perhaps six or seven thousand sheets.

We are just barely moved in, and able to again put our hands on books and files, but are looking forward to the assignment with a great deal of pleasure. Dorothy joins me in warmest regards to you and yours.

As ever,
Paul H. Allen
Botanical Consultant