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 73 · DO #1556 · 40_Slate_Bx2FF2r

Collection
George Lewis Slate (1899–1976) papers on Arnold Arboretum
Item/Folder
Correspondence, Se-Wi, 1954–1966, n.d.
Digital Object
DO #1556, page 73
Collection-level dates
1949–1967, n.d.
Open PDF at page 73 ↗

Page transcription

(9) Practical Plant Breeding. This should concern the application of the science of genetics, the practical application of the knowledge of chromosomes, use of x-ray or colchicine, methods of selection and testing resulting plants, methods of description and methods of introducing valuable new plants into commerce, plant patents, etc.

(10) Propagation. Theoretical studies and their practical application to seeds, cuttings, grafts, etc., with various hormones and under various conditions such as mist spray, plastic tents, outdoor frames, etc., etc.

(11) Pathology and (12) Entomology. These should be studied in relation to both wild and to cultivated plants and under widely different conditions, as well as in relation to ecology, physiology, nutrition, light and temperature, already noted above, and how these may also be affected by plant breeding and selection.

(13) Morphology and (14) Cytology and (15) Anatomy. These may or may not be directly useful to horticulture. A knowledge of these sciences, however, is important in adding understanding to many of the subjects above.

The above fifteen fields for research are not the only ones in which further knowledge is needed, but seem sufficient for the present discussion. Much work in them has already been done by botanists and by horticulturists in widely scattered fields, but as far as is known there has been no continued research by top horticulturists and botanists working together on the same problems concerning cultivated ornamental plants in any given area.