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b9c562f6_guide_to_the_World_of_Warcraft__22 | [0] Gruul's Lair [1] Cleared [2] Cleared [3] Cleared [4] Cleared [5] Cleared [6] Cleared [7] Cleared [8] Cleared [9] Cleared [10] Cleared [11] Cleared [12] Cleared [13] Cleared [14] Cleared [15] Cleared [16] Cleared [17] Cleared [18] Cleared [19] Cleared [20] Cleared [21] Cleared [23] Cleared [24] Cleared [25] Cleared [22] | Cleared | [
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b9c562f6_guide_to_the_World_of_Warcraft__22 | [0] Mount Hyjal [1] Cleared [2] Cleared [3] Cleared [4] Cleared [5] Cleared [6] Cleared [7] Cleared [8] Cleared [9] Cleared [10] Cleared [11] Cleared [12] Cleared [13] Azgalor [14] Cleared [15] Cleared [16] Azgalor [17] Azgalor [18] Azgalor [19] Azgalor [20] Kaz'rogal [21] Azgalor [23] Azgalor [24] Anetheron [25] Anetheron [22] | Azgalor | [
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b9c562f6_guide_to_the_World_of_Warcraft__22 | [0] The Black Temple [1] Cleared [2] Cleared [3] Cleared [4] Cleared [5] Cleared [6] Cleared [7] Cleared [8] Cleared [9] Illidari Council [10] Mother Shahraz [11] - [12] Mother Shahraz [13] Reliquary of Souls [14] Shade of Akama [15] Reliquary of Souls [16] Teron Gorefiend [17] Shade of Akama [18] Shade of Akama [19] Supremus [20] Supremus [21] Shade of Akama [23] Reliquary of Souls [24] Shade of Akama [25] Shade of Akama [22] | Shade of Akama | [
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b9c562f6_guide_to_the_World_of_Warcraft__22 | [0] Sunwell Plateau [1] Cleared [2] Cleared [3] Cleared [4] M'uru [5] Cleared [6] Felmyst [7] Kalecgos [8] Kalecgos [9] - [10] - [11] Brutallus [12] - [13] - [14] Kalecgos [15] - [16] - [17] - [18] - [19] - [20] - [21] - [23] - [24] - [25] - [22] | - | [
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05036e70_inals_system__2_in_MLB___Scout__3 | [0] NLC Org. [1] Pirates [2] Cardinals [4] Reds [5] Brewers [3] | Cubs | [
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05036e70_inals_system__2_in_MLB___Scout__3 | [0] Hitting [1] A- [2] B [4] C [5] C+ [3] | A | [
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05036e70_inals_system__2_in_MLB___Scout__3 | [0] Pitching [1] A [2] A [4] B [5] B- [3] | C+ | [
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05036e70_inals_system__2_in_MLB___Scout__3 | [0] Depth [1] A- [2] A [4] B- [5] C [3] | C | [
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05036e70_inals_system__2_in_MLB___Scout__3 | [0] Overall [1] A [2] A [4] B- [5] C [3] | B+ | [
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9f30a067_ree_Email_Providers___FEPG_net__20 | [1] Elvis.com [2] Email.com [3] EntireWeb [4] Eudora Web-Mail [5] Excite [7] FasterMail [8] FishHoo [9] FitMommies [10] FlashMail.com1 [11] Fresno Mail [13] GameDev.net [14] Garfield Mail [15] GH2000 [16] Go2Net [17] GoHip! [18] GO Network [21] Headbone Zone [22] HerSpace [23] Hotmail [24] Houston Astros (@astrosfan.net) [20] | HamptonRoads | [
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9f30a067_ree_Email_Providers___FEPG_net__20 | [0] Definable Reply-To Address [1] Yes [2] No [3] No [4] No [5] Yes [6] Definable Reply-To Address [7] No [8] No [9] Yes [10] Yes [11] Yes [12] Definable Reply-To Address [13] Yes [14] Yes [15] Yes [16] Yes [17] No [18] No [19] Definable Reply-To Address [21] Yes [22] Yes [23] Yes [24] No [20] | No | [
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e40b5a32_er_Softener___LifeSource_Water__1 | [0] Banned by law in many communities [2] Yes [1] | No | [
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e40b5a32_er_Softener___LifeSource_Water__1 | [0] Removes healthy nutrients from water [2] Yes [1] | No | [
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40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 1 [Threat] Negative [Opportunity] | Positive | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 2 [Threat] May lose, won’t gain [Opportunity] | May gain, won’t lose | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 3 [Threat] Others constrain your actions [Opportunity] | Have means to resolve | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 4 [Threat] Under-qualified to act [Opportunity] | Qualified to act | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 5 [Threat] Resolution initiated by others [Opportunity] | Have Autonomy | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 6 [Threat] Resolution unlikely [Opportunity] | Resolution is likely | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 7 [Threat] Must act, pressured [Opportunity] | Have choice whether to act | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 8 [Threat] Embedded in the past [Opportunity] | Future focused | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 9 [Threat] Action brings no benefits [Opportunity] | Benefits come from acting vs inaction | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 10 [Opportunity] | Stimulating | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 11 [Threat] Personal loss from acting [Opportunity] | Can gain personal advantage | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 12 [Threat] Desire no association [Opportunity] | Want association | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 13 [Threat] Not responsible [Opportunity] | Have responsibility | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 14 [Threat] Issue is visible [Opportunity] | Issue is visible | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 15 [Threat] One solution [Opportunity] | Many solutions vs one solution | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 16 [Opportunity] | Unique | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 17 [Threat] Conflict about how to resolve; Resolution will be by chance [Opportunity] | Agree how to resolve | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 18 [Threat] Difficult to resolve [Opportunity] | Easy to resolve | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 19 [Opportunity] | Obvious Solution | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 20 [Threat] Crisis [Opportunity] | Not crisis | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 21 [Threat] Urgent; Not urgent [Opportunity] | Urgent | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 23 [Threat] Future no better when resolved [Opportunity] | Future better if issue resolved | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 24 [Opportunity] | Enduring vs Temporary | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 25 [Opportunity] | Pressure, vs No pressure | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 26 [Threat] Stress-full [Opportunity] | Stress-full | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 27 [Threat] Success or failure visible [Opportunity] | Success or failure visible | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 28 [Threat] Ambiguous priorities [Opportunity] | High priority | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 29 [Threat] Consequences / implications for the future [Opportunity] | Consequences / implications for the future | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 30 [Threat] Challenge [Opportunity] | Challenge | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
40c1631c_omy__Smart_Opportunity_Windows__Opportunity | [0] 31 [Opportunity] | In direct competition with other opportunities | [] | Smart Economy: Smart Opportunity Windows | Opportunity | http://smarteconomy.typepad.com/smart_economy/smart_opportunity_windows/ | 39/1438042989126.22_20150728002309-00342-ip-10-236-191-2_223639533_1.json |
83af82d3_Costume___Littlegeeky___Rarity__1 | [0] Skirt [2] Complete [1] | High | [
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83af82d3_Costume___Littlegeeky___Rarity__1 | [0] Wig [2] Complete [1] | High | [
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83af82d3_Costume___Littlegeeky___Rarity__1 | [0] Heels [2] Complete [1] | Medium | [
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83af82d3_Costume___Littlegeeky___Rarity__1 | [0] Make-up [2] Complete [1] | Medium | [
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83af82d3_Costume___Littlegeeky___Rarity__1 | [0] Glasses [2] Complete [1] | Low | [
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83af82d3_Costume___Littlegeeky___Rarity__1 | [0] Shirt [2] Complete [1] | Low | [
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[
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83af82d3_Costume___Littlegeeky___Rarity__1 | [0] Cutie mark [2] Complete [1] | Low | [
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83af82d3_Costume___Littlegeeky___Rarity__1 | [0] Contacts [2] Complete [1] | Low | [
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41ed3bfc_e_with_Software_Uninstall_tool__1 | [0] Forcibly uninstall [2] No [1] | Yes | [
[
"Y",
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] | Best Removal Tool - Uninstall Mozilla Firefox,Uninstall Software and Remove Software with Software Uninstall tool | 1 | http://www.bestremovaltool.com/?k=uninstall+Mozilla+Firefox&tid=d98493 | 39/1438042989126.22_20150728002309-00272-ip-10-236-191-2_322384706_2.json |
41ed3bfc_e_with_Software_Uninstall_tool__1 | [0] Forcibly uninstall Corrupted software [2] No [1] | Yes | [
[
"Y",
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[
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"e",
"a",
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] | Best Removal Tool - Uninstall Mozilla Firefox,Uninstall Software and Remove Software with Software Uninstall tool | 1 | http://www.bestremovaltool.com/?k=uninstall+Mozilla+Firefox&tid=d98493 | 39/1438042989126.22_20150728002309-00272-ip-10-236-191-2_322384706_2.json |
41ed3bfc_e_with_Software_Uninstall_tool__1 | [0] Registry Entries Clean [2] Poor [1] | Great | [
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[
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] | Best Removal Tool - Uninstall Mozilla Firefox,Uninstall Software and Remove Software with Software Uninstall tool | 1 | http://www.bestremovaltool.com/?k=uninstall+Mozilla+Firefox&tid=d98493 | 39/1438042989126.22_20150728002309-00272-ip-10-236-191-2_322384706_2.json |
41ed3bfc_e_with_Software_Uninstall_tool__1 | [0] Forcibly Display/Uninstll Hidden software [2] No [1] | Yes | [
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41ed3bfc_e_with_Software_Uninstall_tool__1 | [0] Show Details Of software [2] Poor [1] | Great | [
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41ed3bfc_e_with_Software_Uninstall_tool__1 | [0] Speed [2] Poor [1] | Great | [
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] | Best Removal Tool - Uninstall Mozilla Firefox,Uninstall Software and Remove Software with Software Uninstall tool | 1 | http://www.bestremovaltool.com/?k=uninstall+Mozilla+Firefox&tid=d98493 | 39/1438042989126.22_20150728002309-00272-ip-10-236-191-2_322384706_2.json |
65e9c00d_r__Michael_H__Yost___Paperback__Man_Cave | [0] Who's allowed [Boyhood Fort] Not girls—they have cooties [Man Cave] | Not women—they have authority | [] | The Man Cave Book - Jeff Wilser, Michael H. Yost - Paperback | Man Cave | http://www.harpercollins.com/9780062003928/the-man-cave-book | 39/1438042989126.22_20150728002309-00202-ip-10-236-191-2_485699340_0.json |
65e9c00d_r__Michael_H__Yost___Paperback__Man_Cave | [0] Primary materials used in construction [Boyhood Fort] Wood, stuff your mom doesn't want [Man Cave] | Particleboard, stuff your wife doesn't want | [] | The Man Cave Book - Jeff Wilser, Michael H. Yost - Paperback | Man Cave | http://www.harpercollins.com/9780062003928/the-man-cave-book | 39/1438042989126.22_20150728002309-00202-ip-10-236-191-2_485699340_0.json |
65e9c00d_r__Michael_H__Yost___Paperback__Man_Cave | [0] Key activities inside [Boyhood Fort] Goofing around, avoiding responsibility [Man Cave] | Goofing around, avoiding responsibility | [] | The Man Cave Book - Jeff Wilser, Michael H. Yost - Paperback | Man Cave | http://www.harpercollins.com/9780062003928/the-man-cave-book | 39/1438042989126.22_20150728002309-00202-ip-10-236-191-2_485699340_0.json |
65e9c00d_r__Michael_H__Yost___Paperback__Man_Cave | [0] Peak periods of use [Boyhood Fort] After school, weekends [Man Cave] | After work, weekends | [] | The Man Cave Book - Jeff Wilser, Michael H. Yost - Paperback | Man Cave | http://www.harpercollins.com/9780062003928/the-man-cave-book | 39/1438042989126.22_20150728002309-00202-ip-10-236-191-2_485699340_0.json |
65e9c00d_r__Michael_H__Yost___Paperback__Man_Cave | [0] Slumber parties with buddies? [Boyhood Fort] Yes [Man Cave] | No | [] | The Man Cave Book - Jeff Wilser, Michael H. Yost - Paperback | Man Cave | http://www.harpercollins.com/9780062003928/the-man-cave-book | 39/1438042989126.22_20150728002309-00202-ip-10-236-191-2_485699340_0.json |
65e9c00d_r__Michael_H__Yost___Paperback__Man_Cave | [0] Food and beverages consumed [Boyhood Fort] Soda and unhealthy snacks [Man Cave] | Beer and unhealthy snacks | [] | The Man Cave Book - Jeff Wilser, Michael H. Yost - Paperback | Man Cave | http://www.harpercollins.com/9780062003928/the-man-cave-book | 39/1438042989126.22_20150728002309-00202-ip-10-236-191-2_485699340_0.json |
Dataset Card for "UnpredicTable-cluster24" - Dataset of Few-shot Tasks from Tables
Dataset Summary
The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance.
There are several dataset versions available:
UnpredicTable-full: Starting from the initial WTC corpus of 50M tables, we apply our tables-to-tasks procedure to produce our resulting dataset, UnpredicTable-full, which comprises 413,299 tasks from 23,744 unique websites.
UnpredicTable-unique: This is the same as UnpredicTable-full but filtered to have a maximum of one task per website. UnpredicTable-unique contains exactly 23,744 tasks from 23,744 websites.
UnpredicTable-5k: This dataset contains 5k random tables from the full dataset.
UnpredicTable data subsets based on a manual human quality rating (please see our publication for details of the ratings):
UnpredicTable data subsets based on the website of origin:
- UnpredicTable-baseball-fantasysports-yahoo-com
- UnpredicTable-bulbapedia-bulbagarden-net
- UnpredicTable-cappex-com
- UnpredicTable-cram-com
- UnpredicTable-dividend-com
- UnpredicTable-dummies-com
- UnpredicTable-en-wikipedia-org
- UnpredicTable-ensembl-org
- UnpredicTable-gamefaqs-com
- UnpredicTable-mgoblog-com
- UnpredicTable-mmo-champion-com
- UnpredicTable-msdn-microsoft-com
- UnpredicTable-phonearena-com
- UnpredicTable-sittercity-com
- UnpredicTable-sporcle-com
- UnpredicTable-studystack-com
- UnpredicTable-support-google-com
- UnpredicTable-w3-org
- UnpredicTable-wiki-openmoko-org
- UnpredicTable-wkdu-org
UnpredicTable data subsets based on clustering (for the clustering details please see our publication):
- UnpredicTable-cluster00
- UnpredicTable-cluster01
- UnpredicTable-cluster02
- UnpredicTable-cluster03
- UnpredicTable-cluster04
- UnpredicTable-cluster05
- UnpredicTable-cluster06
- UnpredicTable-cluster07
- UnpredicTable-cluster08
- UnpredicTable-cluster09
- UnpredicTable-cluster10
- UnpredicTable-cluster11
- UnpredicTable-cluster12
- UnpredicTable-cluster13
- UnpredicTable-cluster14
- UnpredicTable-cluster15
- UnpredicTable-cluster16
- UnpredicTable-cluster17
- UnpredicTable-cluster18
- UnpredicTable-cluster19
- UnpredicTable-cluster20
- UnpredicTable-cluster21
- UnpredicTable-cluster22
- UnpredicTable-cluster23
- UnpredicTable-cluster24
- UnpredicTable-cluster25
- UnpredicTable-cluster26
- UnpredicTable-cluster27
- UnpredicTable-cluster28
- UnpredicTable-cluster29
- UnpredicTable-cluster-noise
Supported Tasks and Leaderboards
Since the tables come from the web, the distribution of tasks and topics is very broad. The shape of our dataset is very wide, i.e., we have 1000's of tasks, while each task has only a few examples, compared to most current NLP datasets which are very deep, i.e., 10s of tasks with many examples. This implies that our dataset covers a broad range of potential tasks, e.g., multiple-choice, question-answering, table-question-answering, text-classification, etc.
The intended use of this dataset is to improve few-shot performance by fine-tuning/pre-training on our dataset.
Languages
English
Dataset Structure
Data Instances
Each task is represented as a jsonline file and consists of several few-shot examples. Each example is a dictionary containing a field 'task', which identifies the task, followed by an 'input', 'options', and 'output' field. The 'input' field contains several column elements of the same row in the table, while the 'output' field is a target which represents an individual column of the same row. Each task contains several such examples which can be concatenated as a few-shot task. In the case of multiple choice classification, the 'options' field contains the possible classes that a model needs to choose from.
There are also additional meta-data fields such as 'pageTitle', 'title', 'outputColName', 'url', 'wdcFile'.
Data Fields
'task': task identifier
'input': column elements of a specific row in the table.
'options': for multiple choice classification, it provides the options to choose from.
'output': target column element of the same row as input.
'pageTitle': the title of the page containing the table.
'outputColName': output column name
'url': url to the website containing the table
'wdcFile': WDC Web Table Corpus file
Data Splits
The UnpredicTable datasets do not come with additional data splits.
Dataset Creation
Curation Rationale
Few-shot training on multi-task datasets has been demonstrated to improve language models' few-shot learning (FSL) performance on new tasks, but it is unclear which training tasks lead to effective downstream task adaptation. Few-shot learning datasets are typically produced with expensive human curation, limiting the scale and diversity of the training tasks available to study. As an alternative source of few-shot data, we automatically extract 413,299 tasks from diverse internet tables. We provide this as a research resource to investigate the relationship between training data and few-shot learning.
Source Data
Initial Data Collection and Normalization
We use internet tables from the English-language Relational Subset of the WDC Web Table Corpus 2015 (WTC). The WTC dataset tables were extracted from the July 2015 Common Crawl web corpus (http://webdatacommons.org/webtables/2015/EnglishStatistics.html). The dataset contains 50,820,165 tables from 323,160 web domains. We then convert the tables into few-shot learning tasks. Please see our publication for more details on the data collection and conversion pipeline.
Who are the source language producers?
The dataset is extracted from WDC Web Table Corpora.
Annotations
Annotation process
Manual annotation was only carried out for the UnpredicTable-rated-low, UnpredicTable-rated-medium, and UnpredicTable-rated-high data subsets to rate task quality. Detailed instructions of the annotation instructions can be found in our publication.
Who are the annotators?
Annotations were carried out by a lab assistant.
Personal and Sensitive Information
The data was extracted from WDC Web Table Corpora, which in turn extracted tables from the Common Crawl. We did not filter the data in any way. Thus any user identities or otherwise sensitive information (e.g., data that reveals racial or ethnic origins, sexual orientations, religious beliefs, political opinions or union memberships, or locations; financial or health data; biometric or genetic data; forms of government identification, such as social security numbers; criminal history, etc.) might be contained in our dataset.
Considerations for Using the Data
Social Impact of Dataset
This dataset is intended for use as a research resource to investigate the relationship between training data and few-shot learning. As such, it contains high- and low-quality data, as well as diverse content that may be untruthful or inappropriate. Without careful investigation, it should not be used for training models that will be deployed for use in decision-critical or user-facing situations.
Discussion of Biases
Since our dataset contains tables that are scraped from the web, it will also contain many toxic, racist, sexist, and otherwise harmful biases and texts. We have not run any analysis on the biases prevalent in our datasets. Neither have we explicitly filtered the content. This implies that a model trained on our dataset may potentially reflect harmful biases and toxic text that exist in our dataset.
Other Known Limitations
No additional known limitations.
Additional Information
Dataset Curators
Jun Shern Chan, Michael Pieler, Jonathan Jao, Jérémy Scheurer, Ethan Perez
Licensing Information
Apache 2.0
Citation Information
@misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
}
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