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 30 · DO #1236 · 53_Arber_AN5r

Collection
Agnes Robertson Arber (1879–1960) papers
Item/Folder
Notebook An 5 -- "Herbals and Herbalists", 1901–1904
Digital Object
DO #1236, page 30
Collection-level dates
1886–1985
Open PDF at page 30 ↗

Page transcription

54
Thomas Johnson, Edith & Gertrude's husband, was an
acquaintance of Parkinson
Gerard's garden in Holborn Enlarged near 1100
Sort of plants
Johnson was bred an apothecary in London. The
apothecary before herbals shops on New Hill
He was killed at the Siege of Basing fighting in
The Royalist side
Johnson, if not the first, was among the
earliest botanists who visited Wales Snowdon,
with the sole intention of discovering the rarities
of that country in the vegetative kingdom. The first
found the yellow poppy, papaver cambricum, the
Mountain saxifrage & the rose root, rhodora rosea

55
The Herball or Generall Historie of Plants
Gathered by John Gerard of London Master in
Chirurgie.
Very much enlarged & amended by Thomas
Johnson Citizen & Apothecary of London 1633
(first published 1597)
He quotes Turner, Lyte's translation of Dodonaeus, says there
has been nothing since
Judas Solomon, Theophrastus, Dioscorides, Aristotle
Pliny Galen
Fuchius "his generall method is after the Greek Alphabet"
"He hath taken many of his descriptions as also
various word for word out of the Ancients."
Matthews "runs into many errors, & some of them
wilful ones, so when he gives figures formed by his
own fancy, + o + falsified otherwise in part,
the latter to make them agree with Dioscoris. his
description."
Cesalpino "maketh the Chief affinity of Plants
to consist in the similitude of their seeds & seed vessels.
Gerard bases his herbal, without acknowledgment,
on Priest's translation of Dodonaeus. Mutat verba.