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 94 · DO #4679 · 231_Rogers_Bx3FF2_r

Collection
David James Rogers (1918–2007) papers
Item/Folder
Scientific Reviews, 1971–1972
Digital Object
DO #4679, page 94
Collection-level dates
1948–1977
Open PDF at page 94 ↗

Page transcription

striking similarity to the eyes of the untrained ethnographer.
Since manioc is rather uniform in its gross morphological
characteristics, such differentiation on the part of primitive
ethnobotanists will be of considerable interest to the
anthropologist interested in perception and classification of
the natural world.

The basic taxonomic structure of the Aguaruna plant world appears
to conform in many respects to plant taxonomies found in primitive societies
elsewhere in the world and provides further evidence on the nature of
pre-scientific systems of classification (Berlin, Breedlove and Raven 1966, 1968,
in preparation; Berlin n.d., 1969, 1970; Conklin 1954). There is, for example,
no single linguistic expression for 'plant' in general. On the other hand, at
least three major classes, referring to major life-forms, are recognized
linguistically-- númi 'tree', daék 'vine' and dápa 'herbaceous plant'. Again,
in conformity with primitive principles of classification of the plant world which
appear to be highly general, culturally significant and morphologically aberrant
plants are conceptually treated as separate botanical classes (cf. Berlin,
Breedlove and Raven 1968; Berlin, Breedlove, Laughlin and Raven in press).
Thus, all palms are given distinct names and are not included in the class
tree'. Likewise, ferns, epiphytes and other morphologically aberrant forms are
considered as unique, unaffiliated taxa. All cultivated plants, e.g., manioc,
yams, corn, peanuts, etc. are separate taxa regardless of morphological
characters which might place them in one of the three major classes.

Nomenclaturally, Aguaruna plant names follow strict linguistic
principles which have been suggested elsewhere to be universal (Berlin in
preparation, n.d., 1969). Thus, the vast majority of names are monomial
generic expressions and only a very restricted set of plant names are binomial
specifics. Binomial nomenclature appears to refer to cultivated plants such as
manioc, e.g., dáya máma, púmkum máma, úmiy máma, etc.; sweet potato,
e.g., káye idáuk, kukúyu idáuk, apáy idáuk, etc., or the like. This finding,