This is the data used in this demo site: http://homes.soic.indiana.edu/stsutsui/machine_reading/

The detail is in this paper:

Tsutsui, S., Ding, Y, Meng, G, Machine Reading Approach to Understand Alzheimer's Disease Literature, ACM 10th International Workshop on Data and Text Mining in Biomedical Informatics (DTMBIO), In conjunction with ACM 25th Conference on Information and Knowledge Management (CIKM), Indianapolis, USA, October 24-28, 2016

I store the extracted triples into mysql. So I provide as a dump file that can be imported to MySQL.

MySQL dump (in case you need it):

https://drive.google.com/open?id=0B046sNk0DhCDMVJXQ2hXaUlqTWc

To import data into mysql, use this command.

mysql -u username -p database_name < ad_reverb.sql

* make sure you created database (database_name) in advance

Table name ad_reverb

Current Table Structure.

table:triples

name

type

description

refer to

pmid

INT

pubmed id (id for each article)

years.pmid

s

VARCHER(255)

normalized subject

p

VARCHER(255)

normalized predicate

o

VARCHER(255)

normalized object

s_raw

VARCHER(255)

raw subject as it is in the sentence

p_raw

VARCHER(255)

raw predicate as it is in the sentence

o_raw

VARCHER(255)

raw objectas it is in the sentence

conf

FLOAT

condifence value for the triple

sent_id

INT

sentence id

sentences.sent_id

table:genes

name

type

description

refer to

id

INT

gene id

full_name

VARCHER(255)

gene full name (ex:APOE)

symbol

VARCHER(255)

gene symbol (ex: Apolipoprotein E)

table:years

name

type

description

refer to

pmid

INT

pubmed id

triples.pmid

year

INT

year that the paper is published

table:sentences

name

type

description

refer to

sent_id

INT

sentence_id

sentences.sent_id

sentence

TEXT

sentence