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Where on Earth Do Users Say They Are?: Geo-Entity Linking for Noisy
  Multilingual User Input

Where on Earth Do Users Say They Are?: Geo-Entity Linking for Noisy Multilingual User Input

29 April 2024
Tessa Masis
Brendan O'Connor
ArXivPDFHTML

Papers citing "Where on Earth Do Users Say They Are?: Geo-Entity Linking for Noisy Multilingual User Input"

2 / 2 papers shown
Title
GeoReasoner: Reasoning On Geospatially Grounded Context For Natural
  Language Understanding
GeoReasoner: Reasoning On Geospatially Grounded Context For Natural Language Understanding
Yibo Yan
Joey Lee
LRM
43
6
0
21 Aug 2024
SpaBERT: A Pretrained Language Model from Geographic Data for Geo-Entity
  Representation
SpaBERT: A Pretrained Language Model from Geographic Data for Geo-Entity Representation
Zekun Li
Jina Kim
Yao-Yi Chiang
Muhao Chen
87
27
0
21 Oct 2022
1