CPL @1095 (97.4%) on 17-jan-2018 [ "large retailers , including _" "retailers like _" "discounters like _" "employers such as _" "companies like _" "discount stores such as _" "companies , including _" "bellwethers like _" ] using target_corp
SEAL @628 (63.3%) on 26-aug-2012 [ 12 ] using target_corporation
CPL @1098 (90.5%) on 21-jan-2018 [ "retailers , such as _" "nationwide advertisements for _" "retailers like _" "retail companies , including _" "retailers such as _" "larger retailers , such as _" "mass merchants such as _" "anchor tenant is _" "retail brands such as _" "merchants such as _" "store division of _" "large retailers including _" "retailers , including _" "nationwide class action against _" "retailers including _" "Blind sued _" "retail career with _" "larger retailers such as _" "department store division of _" "_ serves guests" "major sponsorship by _" "big retailers such as _" "centers anchored by _" "discount retailers like _" ] using target_corporation
LE @1072 (66.1%) on 14-aug-2017
SEAL @679 (60.0%) on 04-jan-2013 [ 1 ] using target_corporation
SEAL @721 (59.8%) on 02-apr-2013 [ 123 ] using target_corp
CPL @1095 (94.7%) on 17-jan-2018 [ "large retailers , including _" "U.S. retailers including _" "retailers like _" "chains like _" "retail chains , like _" "discounters like _" "chains , like _" "U.S. retailers , including _" "Discounters such as _" "chains , including _" "same-store sales at _" "discount stores such as _" "retailers including _" "chains , such as _" "stores such as _" "several chains , including _" "retailers , including _" ] using target_corp
CMC @1104 (99.0%) on 18-mar-2018 [ SUFFIX=get 2.00859 SUFFIX=arget 1.88863 SUFFIX=rget 1.88429 PREFIX=targe 1.74671 PREFIX=targ 1.74594 SUFFIX=et 1.67897 LASTPREFIX=corp 1.22632 FULL_WORDSHAPE=a_a -1.12190 SHORT_WORDSHAPE=a -1.46014 WORDS -4.98469 ] using target_corporation
CMC @1064 (99.9%) on 23-jun-2017 [ SUFFIX=et 2.14630 SUFFIX=get 1.83925 SUFFIX=rget 1.80663 SUFFIX=arget 1.80412 PREFIX=targe 1.75044 PREFIX=targ 1.74069 PREFIX=tar 1.04474 SHORT_WORDSHAPE=a -1.26148 POS=MD -1.29235 WORDS -1.68832 ] using target_corp
CPL @1096 (92.6%) on 18-jan-2018 [ "_ has some cute ones" "_ are instantly redeemable" "cashier at _" "co-tenants include _" "dollar bin at _" "diffusion line for _" "strip mall anchored by _" "super sale at _" "they went shopping at _" "popular retailers such as _" "retail job at _" "requisite trip to _" "shoes were from _" "same aisle at _" "regular stores like _" "something I bought at _" "clothing retailers such as _" "clearance items from _" "I hate shopping at _" "I have not shopped at _" "Yesterday I drove to _" "I have n't shopped at _" "Barbie aisle at _" "_ had some great sales" "_ has the same item" "exclusive lines for _" "giant chains like _" "gear sold at _" "_ 's store shelves" "_ does price matching" "_ have limited shelf space" "_ 's virtual shelves" "large retailer such as _" "mattress pad from _" "isle at _" "_ controlled infusion" "Other stores like _" "_ 's supercenters" "mesh bags at _" "kit sold by _" "large retail stores such as _" "new clothing line at _" "other stores , including _" "merchandisers such as _" "candy section at _" "clothing stores such as _" "kind you get at _" "kitchen section at _" "fishing reel at _" "coupon codes including _" "coupon is redeemable at _" "chains like _" "cheaper ones from _" "click , save _" "camera is available at _" "different retailers , including _" "Friday shopping at _" "I am shopping at _" "you normally shop at _" "bags you get at _" "anything you purchase at _" "variety available at _" "warehouse stores such as _" "store chains , including _" "discount bin at _" "deals online at _" "check-out process at _" "shopping trip at _" "stuff we bought at _" "superstore like _" "things I got at _" "_ also have pharmacies" "_ has an entire aisle" "favorite store was _" "food retailers , including _" "dairy case at _" "hair care products at _" "departmental stores like _" "department store called _" "dollar section at _" "retail channels like _" "_ 's aisles" "DVD set at _" "Friday sale at _" "She was employed at _" "Major retailers , such as _" "They were purchased at _" "large chain stores like _" "nationwide class action against _" "local merchants such as _" "local retailers such as _" "free gift card to _" "print pictures at _" "retail store , such as _" "pharmacy manager at _" "crowded aisles of _" "clearance item at _" "stuff I got at _" "software sold at _" "toy section in _" "shopping sites like _" "they are shopping at _" "stuff bought from _" "anchor tenants such as _" "baby crib at _" "_ being a smaller company" "_ has a Starbucks" "customers shopping at _" "coupon savings at _" "cricket equipment at _" "clearance rack at _" "go shopping at _" "furniture collection at _" "housewares department of _" "generous gift card to _" "big box stores , including _" "big-box retailers such as _" "automotive department at _" "_ sells apparel" "big shops like _" "brand is sold at _" "brand stores such as _" "kit I bought at _" "late-night run to _" "major retailers nationwide , including _" "large customers like _" "one I bought at _" "items were purchased at _" "major retail stores such as _" "jar is from _" "kind sold at _" "mega stores like _" "major retailers , such as _" "_ is a retail giant" "supplies today at _" "stores nationwide including _" "superstore such as _" "quick run into _" "shopping run to _" "shoe stores like _" "retail chains including _" "someone steals from _" "online coupon for _" "new jeans at _" "other retailers , including _" "ones I saw at _" "something I bought from _" "retailers , such as _" "shower curtain from _" "store chains like _" "big-box stores such as _" "affordable line for _" "_ is asking suppliers" "_ now carries a line" "supermarkets such as _" "stuff we buy at _" "time you are shopping at _" "Lotions at _" "Eyewear at _" "I remember shopping at _" "me shop at _" "major sale at _" "large retailers , such as _" "various stores like _" "goods department of _" "duvet cover from _" "glass jars at _" "few good deals at _" "merchandisers including _" "local retailers , such as _" "Major chains such as _" "I have n’t shopped at _" "_ often has good deals" "I now shop at _" "Shopping Center is anchored by _" "National retailers such as _" "Big retailers like _" "Bracelets at _" "Discounters such as _" "baby stuff at _" "appliance section of _" "checkout clerks at _" "dollar bins at _" "card form at _" "cashmere sweaters at _" "complex anchored by _" "department stores such as _" "candy aisle at _" "department store , like _" "box I bought at _" "department store like _" "Headphone Purchases from _" "DVD bin at _" "EEOC alleged _" "Many stores such as _" "department store similar to _" "craft department at _" "cream aisle at _" "chains , like _" "discount rack at _" "discount store like _" "megastores like _" "giant retailers like _" "grocery run to _" "dollar aisle at _" "filters are available at _" "shopping centers such as _" "stores like _" "top retailers including _" "side table from _" "tube socks at _" "strip mall next to _" "cheap items at _" "big box like _" "cashiering at _" "check @ _" "center anchored by _" "cami from _" "center across from _" "socks are from _" "dish towels at _" "big stores , like _" "box retailers like _" "drugstores like _" "large retailers , including _" "major retail outlets such as _" "something you buy at _" "stuff I buy at _" "shopping center is anchored by _" "retailers like _" "retail stores including _" "pharmacy chain stores like _" "reusable shopping bags at _" "random trips to _" "sheet set at _" "shelves are from _" "something cheap at _" "popular stores like _" "shoe shopping at _" "I shop mostly at _" "It 's sold at _" "other stores like _" "retailers worldwide including _" "retail outlets , from _" "retail partners including _" "I was shopping in _" "Friday Sale at _" "It 's only available at _" "Discount retailers such as _" "retail center anchored by _" "prevention officer at _" "retail shops , including _" "online retailers such as _" "online merchants such as _" "retail partners , including _" "retailers similar to _" "sale bin at _" "express lane at _" "box I bought from _" "GC 's to _" "I have bought at _" "Strollers at _" "_ 's clearance rack" "Select Items at _" "Clearance items at _" "I recently bought at _" "frames sold by _" "grocery section of _" "general stores such as _" "fun place like _" "corporate chains such as _" "bottle , available at _" "problem shopping at _" "product found at _" "discount retailers , such as _" "discount store called _" "retailer such as _" "price cuts at _" "reusable bags to _" "shadow box from _" "sale rack at _" "national retail chains such as _" "new underwear at _" "retailer like _" "she had bought at _" "shoes sold at _" "products aisle at _" "frozen food section of _" "_ has a printable coupon" "ones I bought at _" "mega-stores like _" "major stores like _" "major chains like _" "leather shoes at _" "major chains , including _" "shirts sold at _" "super stores like _" "retail space , anchored by _" "several retailers including _" "retail giants including _" "retail stores like _" "discount store such as _" "cute ones at _" "chains , such as _" "one I bought from _" "outlet stores like _" "national retailers , including _" "merchandisers as _" "major outlets such as _" "little kit from _" "_ reported first quarter earnings" "things I needed at _" "weekly shopping at _" "markdown at _" "major department stores such as _" "major chains such as _" "more shopping at _" "brands sold at _" "brand available at _" "big chain like _" "stocking shelves at _" "shoping at _" "such stores as _" "time I shop at _" "stock boy for _" "similar item at _" "store brands from _" "store brands include _" "store cards like _" "other day I was walking through _" "anchor stores like _" "water donated by _" "regular shopper at _" "retailers nationwide , including _" "retail chains , like _" "project anchored by _" "I love shopping at _" "DVD today at _" "I do n't normally shop at _" "Designer Shoes at _" "I 'm shopping at _" "Center anchored by _" "I normally buy at _" "US retailers including _" "Chain stores like _" "Removers at _" "towels are from _" "storage products at _" "stuff you buy at _" "stock purchased at _" "wage job at _" "Toys at _" "_ is the first major retailer" "_ is Roseanne Barr" "couponing at _" "cosmetics aisle of _" "expensive stores like _" "shelves at _" "she is registered at _" "retail chain such as _" "reusable bags at _" "HD DVD player at _" "Retail stores like _" "full description at _" "dishtowels from _" "electronics department of _" "excellent price at _" "few necessities at _" "discount bins at _" "friends shop at _" "home goods at _" "laundry detergent at _" "juicy couture at _" "familiar stores like _" "hourly worker at _" "furniture is from _" "stop shopping at _" "stores , such as _" "shopping centers like _" "toy aisle of _" "similar ones at _" "major stores including _" "local stores such as _" "mainstream stores like _" "own bags to _" "shopping center include _" "shopping trips to _" "something you bought at _" "shoplifting at _" "they cost at _" "big retailers like _" "aisles at _" "_ was the first retailer" "favorite stores , including _" "giant retailers such as _" "bag I bought from _" "_ was the first chain" "book retailers like _" "big box store such as _" "various retail outlets such as _" "time I bought from _" "Major stores include _" "_ 's Black Friday sale" "Mixers at _" "Large retailers such as _" "They 're sold at _" "Dividers at _" "late night run to _" "hot seller at _" "he was shopping at _" "general stores like _" "many retailers such as _" "inhibitors of mammalian _" "music section at _" "large retail stores like _" "large retail chains like _" "_ was Bremen" "box stores such as _" "bargain bin at _" "brand stuff at _" "bulk section of _" "retailers ranging from _" "prepaid cards at _" "retail career with _" "same shopping center as _" ] using target
CMC @1104 (100.0%) on 18-mar-2018 [ SUFFIX=get 1.88308 SUFFIX=arget 1.86317 PREFIX=targe 1.82523 PREFIX=targ 1.82433 SUFFIX=rget 1.82051 SUFFIX=et 1.76629 LASTSUFFIX=et 1.48257 FULL_WORDSHAPE=A -1.20085 WORDS -1.42473 FULL_POS=NN -1.57622 ] using target
Human feedback from NELL.08m.160.SSFeedback.csv @161 on 09-nov-2010 [ concept:website:target generalizations concept:publication Action=(+retailStore) ] using target
SEAL @211 (100.0%) on 17-feb-2011 [ 12345678910 ] using target
Sempasre @1112 (75.0%) on 20-jul-2018 [ "In this case , the open system is the target on Earth , and the addition of photons from the Sun constitutes work ." ] using target
CPL @1100 (94.0%) on 30-jan-2018 [ "discounters like _" "U.S. retailers , including _" "Discounters such as _" "discount stores such as _" "stores such as _" ] using target_corp
CPL @1094 (96.9%) on 01-jan-2018 [ "arg2 chief executive arg1" "arg2 CEO and Chairman arg1" "arg2 Chairman and CEO arg1" "arg2 chairman and chief executive officer arg1" "arg2 President and CEO arg1" ] using (gregg_steinhafel, target)
CPL @1094 (96.9%) on 01-jan-2018 [ "arg2 chief executive arg1" "arg2 CEO and Chairman arg1" "arg2 Chairman and CEO arg1" "arg2 chairman and chief executive officer arg1" "arg2 President and CEO arg1" ] using (target, gregg_steinhafel)
SEAL @353 (50.0%) on 19-jul-2011 [ 1 ] using (gregg_steinhafel, target)
CPL @1094 (98.4%) on 01-jan-2018 [ "arg2 President and Chief Executive arg1" "arg2 chief executive arg1" "arg2 CEO and Chairman arg1" "arg2 Chairman and CEO arg1" "arg2 chairman and chief executive officer arg1" "arg2 President and CEO arg1" ] using (gregg_steinhafel, target)
CPL @1103 (100.0%) on 06-mar-2018 [ "arg1 Jersey is arg2" "arg1 York City was arg2" "arg1 Mexico is arg2" "arg1 York became arg2" "arg1 York Stock Exchange is arg2" "arg1 Hampshire has been arg2" "arg1 York is still arg2" "arg1 Zealand is arg2" "arg1 York was the first arg2" "arg1 Mexico became arg2" "arg1 Orleans has become arg2" "arg1 York has long been arg2" "arg1 York has been arg2" "arg1 York is arg2" "arg1 York has always been arg2" "arg1 Orleans is arg2" "arg1 Orleans has been arg2" "arg1 York State is arg2" "arg1 York City became arg2" "arg1 York had been arg2" "arg1 York is the best arg2" "arg1 York City is arg2" "arg1 York city is arg2" "arg1 Zealand is a great arg2" "arg1 Brunswick is arg2" "arg1 York City has been arg2" "arg1 York as his arg2" ] using (new, target)
OE @806 (86.8%) on 23-jan-2014 [ ] using (new, target)
CPL @1103 (100.0%) on 06-mar-2018 [ "arg1 Jersey is arg2" "arg1 York City was arg2" "arg1 York becomes arg2" "arg1 Mexico is arg2" "arg1 York became arg2" "arg1 York Stock Exchange is arg2" "arg1 Hampshire has been arg2" "arg1 York is still arg2" "arg1 Zealand is arg2" "arg1 York was the first arg2" "arg1 Mexico became arg2" "arg1 Orleans has become arg2" "arg1 York has long been arg2" "arg1 York has been arg2" "arg1 York is arg2" "arg1 York as their arg2" "arg1 Zealand and arg2" "arg1 York has always been arg2" "arg1 Orleans is arg2" "arg1 Orleans has been arg2" "arg1 York State is arg2" "arg1 York City became arg2" "arg1 York had been arg2" "arg1 York is the best arg2" "arg1 York City is arg2" "arg1 York city is arg2" "arg1 Zealand is a great arg2" "arg1 Jersey became arg2" "arg1 Brunswick is arg2" "arg1 York City has been arg2" "arg1 York as his arg2" ] using (new, target)
CPL @1094 (96.9%) on 01-jan-2018 [ "arg2 chief executive arg1" "arg2 CEO and Chairman arg1" "arg2 Chairman and CEO arg1" "arg2 chairman and chief executive officer arg1" "arg2 President and CEO arg1" ] using (gregg_steinhafel, target)
CPL @1116 (93.8%) on 06-sep-2018 [ "arg2 Department of Defense and arg1" "arg2 Geological Survey and arg1" "arg2 Consumer Product Safety Commission and arg1" "arg2 Defense Department and arg1" ] using (target, u_s_)
NELL has only weak evidence for items listed in grey
CPL @1099 (87.5%) on 23-jan-2018 [ "arg2 levels of greenhouse arg1" "arg2 of greenhouse arg1" "arg2 reductions of greenhouse arg1" ] using (gas_emissions, target)
CPL @1095 (98.4%) on 17-jan-2018 [ "arg2 to overtake the United arg1" "arg2 than in the United arg1" "arg2 and the United arg1" "arg2 and then the United arg1" "arg2 country to the United arg1" "arg2 rather than the United arg1" ] using (states, target)
CPL @1095 (87.5%) on 17-jan-2018 [ "arg1 Obama has been arg2" "arg1 Obama is arg2" "arg1 Obama will be the next arg2" ] using (president_barack, target)
CPL @1116 (93.8%) on 06-sep-2018 [ "arg2 Department of Defense and arg1" "arg2 Geological Survey and arg1" "arg2 Consumer Product Safety Commission and arg1" "arg2 Defense Department and arg1" ] using (target, u_s_)
CPL @1104 (75.0%) on 18-mar-2018 [ "arg2 Field home of arg1" "arg2 Field for arg1" ] using (minnesota_twins, target)
CPL @1114 (99.2%) on 18-aug-2018 [ "arg2 Field for arg1" "arg2 Field to cheer on arg1" "arg2 Field against arg1" "arg2 Field to see arg1" "arg2 Field during arg1" "arg2 Field when arg1" "arg2 Field where arg1" ] using (twins, target)
CPL @1096 (96.9%) on 18-jan-2018 [ "arg2 engine we arg1" "arg2 engine to arg1" "arg2 criteria to narrow your arg1" "arg2 engine so that your arg1" "arg2 engines to find your arg1" ] using (target, search)
CPL @1096 (96.9%) on 18-jan-2018 [ "arg2 engine we arg1" "arg2 engine to arg1" "arg2 criteria to narrow your arg1" "arg2 engine so that your arg1" "arg2 engines to find your arg1" ] using (search, target)
CPL @1096 (96.9%) on 18-jan-2018 [ "arg2 engine we arg1" "arg2 engine to arg1" "arg2 criteria to narrow your arg1" "arg2 engine so that your arg1" "arg2 engines to find your arg1" ] using (target, search)
CPL @1096 (96.9%) on 18-jan-2018 [ "arg2 engine we arg1" "arg2 engine to arg1" "arg2 criteria to narrow your arg1" "arg2 engine so that your arg1" "arg2 engines to find your arg1" ] using (search, target)
CPL @1096 (96.9%) on 18-jan-2018 [ "arg2 engine we arg1" "arg2 engine to arg1" "arg2 criteria to narrow your arg1" "arg2 engine so that your arg1" "arg2 engines to find your arg1" ] using (target, search)
CPL @1096 (96.9%) on 18-jan-2018 [ "arg2 engine we arg1" "arg2 engine to arg1" "arg2 criteria to narrow your arg1" "arg2 engine so that your arg1" "arg2 engines to find your arg1" ] using (search, target)
CPL @1096 (96.9%) on 18-jan-2018 [ "arg2 engine we arg1" "arg2 engine to arg1" "arg2 criteria to narrow your arg1" "arg2 engine so that your arg1" "arg2 engines to find your arg1" ] using (target, search)
CPL @1096 (96.9%) on 18-jan-2018 [ "arg2 engine we arg1" "arg2 engine to arg1" "arg2 criteria to narrow your arg1" "arg2 engine so that your arg1" "arg2 engines to find your arg1" ] using (search, target)
CPL @1096 (96.9%) on 18-jan-2018 [ "arg2 engine we arg1" "arg2 engine to arg1" "arg2 criteria to narrow your arg1" "arg2 engine so that your arg1" "arg2 engines to find your arg1" ] using (target, search)
CPL @1096 (96.9%) on 18-jan-2018 [ "arg2 engine we arg1" "arg2 engine to arg1" "arg2 criteria to narrow your arg1" "arg2 engine so that your arg1" "arg2 engines to find your arg1" ] using (search, target)
CPL @1096 (96.9%) on 18-jan-2018 [ "arg2 engine we arg1" "arg2 engine to arg1" "arg2 criteria to narrow your arg1" "arg2 engine so that your arg1" "arg2 engines to find your arg1" ] using (target, search)
CPL @1096 (96.9%) on 18-jan-2018 [ "arg2 engine we arg1" "arg2 engine to arg1" "arg2 criteria to narrow your arg1" "arg2 engine so that your arg1" "arg2 engines to find your arg1" ] using (search, target)
CPL @1094 (100.0%) on 01-jan-2018 [ "arg1 Jersey is arg2" "arg1 York is still arg2" "arg1 York was the first arg2" "arg1 Mexico became arg2" "arg1 York has long been arg2" "arg1 Orleans has been arg2" "arg1 York State is arg2" "arg1 York is the best arg2" "arg1 York City is arg2" "arg1 York city is arg2" "arg1 Zealand is a great arg2" "arg1 York City has been arg2" "arg1 York as his arg2" ] using (target, new)
CPL @1094 (100.0%) on 01-jan-2018 [ "arg1 Jersey is arg2" "arg1 York is still arg2" "arg1 York was the first arg2" "arg1 Mexico became arg2" "arg1 York has long been arg2" "arg1 Orleans has been arg2" "arg1 York State is arg2" "arg1 York is the best arg2" "arg1 York City is arg2" "arg1 York city is arg2" "arg1 Zealand is a great arg2" "arg1 York City has been arg2" "arg1 York as his arg2" ] using (new, target)
CPL @1094 (100.0%) on 01-jan-2018 [ "arg1 Jersey is arg2" "arg1 York is still arg2" "arg1 York was the first arg2" "arg1 Mexico became arg2" "arg1 York has long been arg2" "arg1 Orleans has been arg2" "arg1 York State is arg2" "arg1 York is the best arg2" "arg1 York City is arg2" "arg1 York city is arg2" "arg1 Zealand is a great arg2" "arg1 York City has been arg2" "arg1 York as his arg2" ] using (target, new)
CPL @1094 (100.0%) on 01-jan-2018 [ "arg1 Jersey is arg2" "arg1 York is still arg2" "arg1 York was the first arg2" "arg1 Mexico became arg2" "arg1 York has long been arg2" "arg1 Orleans has been arg2" "arg1 York State is arg2" "arg1 York is the best arg2" "arg1 York City is arg2" "arg1 York city is arg2" "arg1 Zealand is a great arg2" "arg1 York City has been arg2" "arg1 York as his arg2" ] using (new, target)
CPL @1094 (100.0%) on 01-jan-2018 [ "arg1 Jersey is arg2" "arg1 York is still arg2" "arg1 York was the first arg2" "arg1 Mexico became arg2" "arg1 York has long been arg2" "arg1 Orleans has been arg2" "arg1 York State is arg2" "arg1 York is the best arg2" "arg1 York City is arg2" "arg1 York city is arg2" "arg1 Zealand is a great arg2" "arg1 York City has been arg2" "arg1 York as his arg2" ] using (target, new)
CPL @1094 (100.0%) on 01-jan-2018 [ "arg1 Jersey is arg2" "arg1 York is still arg2" "arg1 York was the first arg2" "arg1 Mexico became arg2" "arg1 York has long been arg2" "arg1 Orleans has been arg2" "arg1 York State is arg2" "arg1 York is the best arg2" "arg1 York City is arg2" "arg1 York city is arg2" "arg1 Zealand is a great arg2" "arg1 York City has been arg2" "arg1 York as his arg2" ] using (new, target)
CPL @1094 (100.0%) on 01-jan-2018 [ "arg1 Jersey is arg2" "arg1 York is still arg2" "arg1 York was the first arg2" "arg1 Mexico became arg2" "arg1 York has long been arg2" "arg1 Orleans has been arg2" "arg1 York State is arg2" "arg1 York is the best arg2" "arg1 York City is arg2" "arg1 York city is arg2" "arg1 Zealand is a great arg2" "arg1 York City has been arg2" "arg1 York as his arg2" ] using (target, new)
CPL @1094 (100.0%) on 01-jan-2018 [ "arg1 Jersey is arg2" "arg1 York is still arg2" "arg1 York was the first arg2" "arg1 Mexico became arg2" "arg1 York has long been arg2" "arg1 Orleans has been arg2" "arg1 York State is arg2" "arg1 York is the best arg2" "arg1 York City is arg2" "arg1 York city is arg2" "arg1 Zealand is a great arg2" "arg1 York City has been arg2" "arg1 York as his arg2" ] using (new, target)
CPL @1094 (100.0%) on 01-jan-2018 [ "arg1 Jersey is arg2" "arg1 York is still arg2" "arg1 York was the first arg2" "arg1 Mexico became arg2" "arg1 York has long been arg2" "arg1 Orleans has been arg2" "arg1 York State is arg2" "arg1 York is the best arg2" "arg1 York City is arg2" "arg1 York city is arg2" "arg1 Zealand is a great arg2" "arg1 York City has been arg2" "arg1 York as his arg2" ] using (target, new)
CPL @1094 (100.0%) on 01-jan-2018 [ "arg1 Jersey is arg2" "arg1 York is still arg2" "arg1 York was the first arg2" "arg1 Mexico became arg2" "arg1 York has long been arg2" "arg1 Orleans has been arg2" "arg1 York State is arg2" "arg1 York is the best arg2" "arg1 York City is arg2" "arg1 York city is arg2" "arg1 Zealand is a great arg2" "arg1 York City has been arg2" "arg1 York as his arg2" ] using (new, target)
CPL @1094 (100.0%) on 01-jan-2018 [ "arg1 Jersey is arg2" "arg1 York is still arg2" "arg1 York was the first arg2" "arg1 Mexico became arg2" "arg1 York has long been arg2" "arg1 Orleans has been arg2" "arg1 York State is arg2" "arg1 York is the best arg2" "arg1 York City is arg2" "arg1 York city is arg2" "arg1 Zealand is a great arg2" "arg1 York City has been arg2" "arg1 York as his arg2" ] using (target, new)
CPL @1094 (100.0%) on 01-jan-2018 [ "arg1 Jersey is arg2" "arg1 York is still arg2" "arg1 York was the first arg2" "arg1 Mexico became arg2" "arg1 York has long been arg2" "arg1 Orleans has been arg2" "arg1 York State is arg2" "arg1 York is the best arg2" "arg1 York City is arg2" "arg1 York city is arg2" "arg1 Zealand is a great arg2" "arg1 York City has been arg2" "arg1 York as his arg2" ] using (new, target)