ONTOTEXT (From Text to Knowledge for the Semantic Web)

Oct 1, 2004 | Projects

1 October 2004 to 30 September 2007 - PROJECT CLOSED

Based on the philosophy of the Semantic Web, Ontotext exploits text processing and automatic reasoning technologies to extract knowledge from texts and organise it conceptually in an ontology. Unlike common search engines, the Ontotext Portal directly accesses the concepts and entities of the ontology and presents the user with structured information instead of mere portions of texts. For each entity, the Ontotext Portal offers four different views: Articles (lists all the documents in which it is mentioned), Citografo (shows how often it is mentioned), Opinions (shows how often opinions are expressed about it), and Record (provides extra information about it).

MT Group at FBK Follow

#MachineTranslation Research Unit @FBK_research. #nlproc #deeplearning #ai

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MT Group at FBK

@fbk_mt ·

21 Sep

Our #PickOfTheWeek, selected by @BeatriceSavoldi:

"The AI Observatory: A Public Measure of Real-World AI Use" by @ShayneRedford, @AnkaReuel, @zoeykii et al.

A crucial framework tracking how AI models are deployed, adopted, and evaluated beyond lab benchmarks.

BeatriceSavoldi @BeatriceSavoldi

Pick of the week @fbk_mt
📚"The AI Observatory: A Public Measure of Real-World AI Use"

A study and taxonomy to explore real conversations across multiple datasets.
https://www.dataprovenance.org/ai_observatory.pdf

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MT Group at FBK

@fbk_mt ·

9 Sep

Can algorithmic gender prediction ever be valid?

Check out this week's top pick by @lina_conti: "Algorithmic Gender Prediction Is Illegitimate, But Gender Imputation Can Yield Valid Measurements" by @evandongyx & @ang3linawang.

Lina Conti @lina_conti

Pick of the week by @evandongyx & @ang3linawang:
https://arxiv.org/pdf/2608.13444

Predicting gender from images or names can reveal discrimination. But the practice itself harms trans people. This paper works through when that tradeoff might be justified and how to do it responsibly.

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MT Group at FBK

@fbk_mt ·

3 Sep

Our pick of the week by
@dhairya_su47605
: "Task-Circuit Quantization: Leveraging Knowledge Localization and Interpretability for Compression" by @hanqi_xiao, @yilin_sung, @EliasEskin and @mohitban47
#Quantization #Interpretibility

Dhairya Suman @dhairya_su47605

#PickoftheWeek @fbk_mt
Super cool paper on leavaraging Interpretability for Compression!

https://arxiv.org/pdf/2504.07389

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MT Group at FBK

@fbk_mt ·

12 Aug

Our pick of the week:

"Large Language Diffusion Model" by Shen Nie, Fengqi Zhu, @ZebinYou, Xiaolu Zhang, Jingyang Ou, Jun Hu, Jun Zhou, Yankai Lin, Ji-Rong Wen, @LiChongxuan

It is very cool to see how the researcher combine diffusion model and transformer blocks to train

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