whataboutyou-ai/financial_bert
Token Classification • 0.1B • Updated • 31 • 1
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EX-99.1
EX-99.1
PRESS RELEASE
Columbia Equity Trust, Inc. [Logo]
1750 H Street, NW
Suite 500
Washington, D.C. 20006
Tel (202) 303 - 3080
________________________________________________
Columbia Equity Trust, Inc. Announces $34.1 Million Acquisition
Washington, D.C., January 13, 2006 - Columbia E... | [
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Exhibit 99.1
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Exhibit 99.1
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EX-99.1
Exhibit 99.1
Media Contact:
IR Contact
Darris Gringeri
(310) 964-0808
212-205-0882
DIRECTV Completes Merger Transaction with
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EL
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1308606-000129993306000993-exhibit1 | EX-99.1
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EX-99.1
EX-99.1
C O L E
COLE CREDIT PROPERTY TRUST II, INC.
February 14, 2006
Contact:
John H. Lotka, Chief Marketing Officer
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Cole Credit Property Trust II, Inc. announces the acquisition of a single-tenant retail
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7332-000000733220000079-swn-20201113xexhibit991 | EX-99.1
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EX-99.1 PRESS RELEASE - MERGER
Document
NEWS RELEASE
SOUTHWESTERN ENERGY COMPLETES ACQUISITION OF MONTAGE RESOURCES
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1301236-000156459019035909-soho-ex991_75 | EX-99.1
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EX-99.1
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Exhibit 99.1
FOR IMMEDIATE RELEASE
MONDAY, SEPTEMBER 30, 2019
SOTHERLY HOTELS INC. ANNOUNCES ACQUISITON OF
CONDO HOTEL COMMERCIAL UNIT
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1005229-000100522906000017-fcsalepr | EX-99
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PRESS RELEASE
NEWS RELEASE
CONTACT:
Karen L. Howard
Vice President - Finance and Chief Financial Officer
Columbus McKinnon Corporation
716-689-5550
COLUMBUS MCKINNON COMPLETES SALE OF
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PRESS RELEASE
ptx_ex991.htm
EXHIBIT 99.1
Pernix Contact:
Joseph T. Schepers
Director, Investor Relations
(800) 793-2145 ext. 3002
[email protected]
Pernix Therapeutics Completes Acquisition of Somaxon Pharmaceuticals, Inc.
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1043382-000104338210000014-exhibit_99-1 | EX-99.1
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EXHIBIT 99.1 - PRESS RELEASE
exhibit_99-1.htm
Exhibit 99.1
NEWS
FOR IMMEDIATE RELEASE
Solutia Inc.
575 Maryville Centre Drive
St. Louis, Missouri 63141
P.O. Box 66760
St. Louis, Missouri 63166-6760
Media:
Melissa Zona (314) 674-5555
Investors:
Susannah Livingston (314) 674-8914
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48465-000110465913006551-a13-4060_1ex99 | EX-99
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EX-99
Exhibit 99
Contact:
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507-437-5345
[email protected]
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1069899-000157104916011076-t1600238_ex99-1 | EX-99.1
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EXHIBIT 99.1
Exhibit 99.1
For Immediate Release
Phibro Animal Health Corporation Announces Closing of Acquisition
of Business of MVP Laboratories, Inc.
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BUSiness Transaction Entity Recognition dataset.
BUSTER is an Entity Recognition (ER) benchmark for entities related to business transactions. It consists of a gold corpus of 3779 manually annotated documents on financial transactions that were randomly divided into 5 folds, plus an additional silver corpus of 6196 automatically annotated documents that were created by the model-optimized RoBERTa system.
| Gold | Silver | |||||||
|---|---|---|---|---|---|---|---|---|
| fold 1 | fold 2 | fold 3 | fold 4 | fold 5 | Total | Total | ||
| N. Docs | 753 | 759 | 758 | 755 | 754 | 3779 | 6196 | |
| N. Tokens | 685K | 680K | 687K | 697K | 688K | 3437K | 5647K | |
| N. Annotations | 4119 | 4267 | 4100 | 4103 | 4163 | 20752 | 33272 | |
You can find the pre-print here.
If you use BUSTER in your work, please cite us:
@inproceedings{zugarini-etal-2023-buster,
title = "{BUSTER}: a {``}{BUS}iness Transaction Entity Recognition{''} dataset",
author = "Zugarini, Andrea and
Zamai, Andrew and
Ernandes, Marco and
Rigutini, Leonardo",
editor = "Wang, Mingxuan and
Zitouni, Imed",
booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: Industry Track",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.emnlp-industry.57",
doi = "10.18653/v1/2023.emnlp-industry.57",
pages = "605--611",
abstract = "Albeit Natural Language Processing has seen major breakthroughs in the last few years, transferring such advances into real-world business cases can be challenging. One of the reasons resides in the displacement between popular benchmarks and actual data. Lack of supervision, unbalanced classes, noisy data and long documents often affect real problems in vertical domains such as finance, law and health. To support industry-oriented research, we present BUSTER, a BUSiness Transaction Entity Recognition dataset. The dataset consists of 3779 manually annotated documents on financial transactions. We establish several baselines exploiting both general-purpose and domain-specific language models. The best performing model is also used to automatically annotate 6196 documents, which we release as an additional silver corpus to BUSTER.",
}