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 7 · 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 7
Collection-level dates
1937–1963
Open PDF at page 7 ↗

Page transcription

TEXAS RESEARCH FOUNDATION
RENNER, TEXAS

September 6, 1958

Mr. Paul H. Allen
Centro Nacional de Agronomia
Santa Tecla
El Salvador

Dear Paul:

Thank you for your nice letter. Are you on leave of absence from Zamorano or are you permanently located at your present address? Your work on a timber utilization manual for El Salvador sounds interesting. I spent quite a bit of time with Earl Smith in Peru this spring. He is working on the forest resources of that country. You may remember that he worked on the forest resources of Cuba. I know that you will enjoy your work.

In regard to the duplicate specimens, we should be most grateful to you if you can arrange to send us a set of what you may be able to spare. As you have suggested, we would like to have as good a specimen as possible with locality data and collector, as well as any other information that might be available for the specimen. We should certainly like to have you keep us in mind when you collect in the future. We should be very happy to have you make our herbarium a depository for your collections in the United States. We would see that they are always available to anyone for study and shall certainly let the world know where they are.

I do not know what arrangement you wish to make. We, of course, will defray any expense of getting the specimens to us; packing, shipping, etc. Are you interested in exchange of specimens? I should appreciate your advice along this line. As I mentioned in my previous letter, we would accept material from any Central American country as well as Mexico.

With best regards,

Sincerely yours,
Donovan S. Correll, Head
Botanical Laboratory