Hi everybody,
Join us next Wed, *October 4th, *at 12 PM CT for our monthly webinar. We
will have Pascal Neveu from INRAE (France) talking about the European
EMPHASIS project <https://emphasis.plant-phenotyping.eu/> and PHIS, an
ontology-based information system for plant phenotyping.
I have included below more details about the webinar and the Zoom link to
attend the webinar.
I hope you will join us.
Best,
Annarita
:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:
Presenters: Pascal Neveu, UMR MISTEA, INRAE (France)
Abstract:
*PHIS, an ontology-based Information System for Plant Phenotyping*
The European EMPHASIS infrastructure aims to enable researchers to use
facilities, resources, and services for high-throughput phenotyping of
plants. Within the infrastructure, we are leading actions to help
scientists better understand plant performance and translate this knowledge
into applications. This presentation will look at some examples of data
management and implementation of data standards carried out in this context
to add value to the phenotyping data. In particular, we will look at PHIS,
an ontology-based information system based on the OpenSILEX framework.
*| 1P ET | 12P CT | 11A MT | 10A PT |*
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Topic: AgBioData Monthly Webinar
Time: This is a recurring meeting Meet anytime
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Meeting ID: 820 3835 6125
Passcode: 160683
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Hi everybody,
This is a friendly reminder of our monthly webinar tomorrow, *Sept 6th, *at
12 PM CT for our monthly webinar. We will have* Harry Caufield
<https://github.com/caufieldjh>,* Lawrence Berkeley National Laboratory,
talking about how *SPIRES* implements Large Language Models (LLMs) to
extract structured knowledge in agricultural science and beyond.
I have included below more details about the webinar and the Zoom link to
attend the webinar.
I hope you will join us.
Best,
Annarita
:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:-:
Presenters: Harry Caufield <https://github.com/caufieldjh>, Lawrence
Berkeley National Laboratory
Abstract:
*Staying grounded: assembling structured biological knowledge with help
from large language models*
Developing comprehensive knowledge bases and ontologies demands meticulous
curation. The emergence of highly flexible, artificial intelligence-driven
approaches to natural language processing offers novel ways to expedite
this process. Current methods often rely on extensive training data,
however, and struggle with complex, nested knowledge structures. In this
talk, I will describe a new approach, Structured Prompt Interrogation and
Recursive Extraction of Semantics (SPIRES). This method for information
extraction leverages the capability of Large Language Models (LLMs) to
perform zero-shot learning (ZSL) with a variety of natural-language
prompts. SPIRES operates with predefined data schemas, enabling information
extraction that adheres to these structures. It also grounds concepts with
well-established ontologies and vocabularies, avoiding the "hallucinations"
common to text generated by LLMs.
Within OntoGPT, an LLM-querying framework we have developed, SPIRES
supports rapid application to summarization and modeling across plant
science and biology. Notably, this approach allows customization for new
tasks and topics without a need for new training data. We have found that
OntoGPT and SPIRES are capable of extracting structured knowledge from
large literature collections and constructing knowledge graphs from the
resulting relationships. Through harnessing the language comprehension
capabilities of LLMs, SPIRES streamlines knowledge acquisition from across
agricultural science and beyond.
*| 1P ET | 12P CT | 11A MT | 10A PT |*
Find your local time here
<https://www.timeanddate.com/worldclock/fixedtime.html?msg=September+AgBioDa…>
Topic: AgBioData Monthly Webinar
Time: This is a recurring meeting Meet anytime
Join Zoom Meeting
https://us06web.zoom.us/j/82038356125?pwd=YVFMRElMdEpHZmtObXFvZlA4QVFXQT09
Meeting ID: 820 3835 6125
Passcode: 160683
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Meeting ID: 820 3835 6125
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