In this newsletter:
Maintaining LDC organization user accounts
LDC data and commercial technology development

New publications:
KAIROS Phase 1 Evaluation Source Data, Annotation, and 
Assessment<https://catalog.ldc.upenn.edu/LDC2026T07>
Multi-Language Conversational Telephone Speech 2014 - Spanish & 
Portuguese<https://catalog.ldc.upenn.edu/LDC2026S07>
LORELEI Multiway Translated Text<https://catalog.ldc.upenn.edu/LDC2026T06>

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Maintaining LDC organization user accounts
LDC encourages organization account administrators to review their LDC 
organization user accounts at least annually to remove users who are no longer 
affiliated with the organization. Users no longer affiliated with an 
organization cannot continue to access LDC data through the organization's LDC 
account. As stated in LDC's membership agreements and license agreements, LDC 
data cannot be shared outside the member/licensing organization. LDC reserves 
the right to deactivate user accounts if any suspicious activity is detected. 
Visit the User 
Accounts<https://www.ldc.upenn.edu/members/managing-your-ldc-account/user-accounts>
 page for further information on user types and privileges.

LDC data and commercial technology development
For-profit organizations are reminded that an LDC membership is a pre-requisite 
for obtaining a commercial license to almost all LDC databases. Non-member 
organizations, including non-member for-profit organizations, cannot use LDC 
data to develop or test products for commercialization, nor can they use LDC 
data in any commercial product or for any commercial purpose. LDC data users 
should consult corpus-specific license agreements for limitations on the use of 
certain corpora. Visit the 
Licensing<https://www.ldc.upenn.edu/data-management/using/licensing> page for 
further information.
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New publications:
KAIROS Phase 1 Evaluation Source Data, Annotation, and 
Assessment<https://catalog.ldc.upenn.edu/LDC2026T07> was developed by LDC and 
contains the English and Spanish source data (text, video, images), manual 
annotations, reference knowledge graphs, the system output assessed during the 
evaluation, and human assessment results from the Phase 1 evaluation of the 
DARPA KAIROS Program. The Phase 1 evaluation focused on the improvised 
explosive bombing scenario with nine complex events and two surprise complex 
events in the mass shooting scenario.

Source data for each complex event consisted of 10-15 documents that included 
multimodal English and Spanish event-relevant and off-topic distractor 
documents. Manual annotation and assessment of event-relevant documents for 10 
complex events are included in this release. Scenario-relevant events and 
relations were labeled for each document to develop a structured representation 
of temporally-ordered events, relations, and arguments that expressed the 
scenario-relevant events in each complex event. A reference knowledge graph 
(Graph G) was developed for each event; systems were expected to match the 
Graph G with a given schema library. Assessment data includes human assessment 
judgments and the system output that was manually assessed for the end-to-end 
evaluation task.

The DARPA KAIROS (Knowledge-directed Artificial Intelligence Reasoning Over 
Schemas) program aimed to build technology capable of understanding and 
reasoning about complex real-world events in order to provide actionable 
insights to end users. KAIROS systems utilized formal event representations in 
the form of schema libraries that specified the steps, preconditions, and 
constraints for an open set of complex events; schemas were then used in 
combination with event extraction to characterize and make predictions about 
real-world events in a large multilingual, multimedia corpus.

2026 members can access this corpus through their LDC accounts. Non-members may 
license this data for a fee.

                                                                                
               *

Multi-Language Conversational Telephone Speech 2014 - Spanish & 
Portuguese<https://catalog.ldc.upenn.edu/LDC2026S07> was developed by LDC and 
is comprised of 123 hours of Spanish and Portuguese telephone speech. The data 
was collected to support research and technology evaluation in automatic 
language identification; portions of these recordings were used in the NIST 
2015 and 2017 language recognition 
evaluations<https://www.nist.gov/itl/iad/mltg/language-recognition>. The 
collection focused on language pair discrimination for 20 languages/dialects, 
some of which could be considered mutually intelligible or closely related.

This corpus contains 569 recordings covering Brazilian Portuguese, Caribbean 
Spanish, European Spanish, and Latin American Spanish. Participants were 
recruited by native speakers who contacted acquaintances in their social 
network. Those native speakers made one call, up to 8 minutes, to each 
acquaintance. Human auditors labeled the calls for language, quality, callee 
gender, dialect type, and noise.

2026 members can access this corpus through their LDC accounts. Non-members may 
license this data for a fee.

                                                                                
               *

LORELEI Multiway Translated Text<https://catalog.ldc.upenn.edu/LDC2026T06> 
consists of a fixed set of English texts (around 100,000 words) translated into 
24 languages. It was developed by LDC for the DARPA LORELEI Program; the 
translations were included in the LORELEI representative language packs created 
by LDC in 2016-2019.

The common word set was composed of English news documents (50%), 
LORELEI-domain English news documents (25%), and a phrasebook and elicitation 
corpus (25%). The phrasebook contained everyday colloquial phrases. The 
elicitation corpus was designed to represent linguistic structures. Texts were 
translated by a combination of professional translators and crowd-sourced 
translators.

The LORELEI (Low Resource Languages for Emergent Incidents) program was 
concerned with building human language technology for low resource languages in 
the context of emergent situations like natural disasters or disease outbreaks. 
Linguistic resources for LORELEI include Representative Language Packs and 
Incident Language Packs for over two dozen low resource languages, comprising 
data, annotations, basic natural language processing tools, lexicons, and 
grammatical resources. Representative languages were selected to provide broad 
typological coverage, while incident languages were selected to evaluate system 
performance on a language whose identity was disclosed at the start of the 
evaluation.

2026 members can access this corpus through their LDC accounts. Non-members may 
license this data for a fee.

To unsubscribe from this newsletter, log in to your LDC 
account<https://catalog.ldc.upenn.edu/login> and uncheck the box next to 
"Receive Newsletter" under Account Options or contact LDC for assistance.

Membership Coordinator
Linguistic Data Consortium<ldc.upenn.edu>
University of Pennsylvania
T: +1-215-573-1275
E: [email protected]<mailto:[email protected]>
M: 3600 Market St. Suite 810
      Philadelphia, PA 19104




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