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{"id":333008,"global_id":"Z2lkOi8vaGFja2Vyb25lL1JlcG9ydC8zMzMwMDg=","url":"https://hackerone.com/reports/333008","title":"Persistent XSS in https://sandbox.reverb.com/item/","state":"Closed","substate":"resolved","severity_rating":"high","readable_substate":"Resolved","created_at":"2018-04-03T20:49:11.135Z","submitted_at":"2018-04-03T20:49:11.135Z","is_member_of_team?":false,"reporter":{"disabled":false,"username":"bigshaq","url":"/bigshaq","profile_picture_urls":{"small":"https://profile-photos.hackerone-user-content.com/variants/000/237/280/5980a2efdbaac92c70aca72693147dfaf53f7bba_original.png/43e4513b9104ea0d68c9c096cea374ba8440dde3e027af5465c8771e8839a67c"},"is_me?":false,"cleared":false,"hackerone_triager":false,"hacker_mediation":false},"team":{"id":3094,"url":"https://hackerone.com/reverb","handle":"reverb","profile_picture_urls":{"small":"https://profile-photos.hackerone-user-content.com/variants/000/003/094/b7238acaca15ddb329cf25e69c687352247aece5_original.png/43e4513b9104ea0d68c9c096cea374ba8440dde3e027af5465c8771e8839a67c","medium":"https://profile-photos.hackerone-user-content.com/variants/000/003/094/b7238acaca15ddb329cf25e69c687352247aece5_original.png/fd4ecbe1e3e98c343c7717114485ace2f830f9253103d3cfa7502059868c516c"},"permissions":[],"submission_state":"disabled","default_currency":"usd","awards_miles":false,"offers_bounties":true,"state":"public_mode","only_cleared_hackers":false,"pentest_feature_enabled?":false,"profile":{"name":"Reverb.com","twitter_handle":"reverb","website":"https://sandbox.reverb.com","about":"The best place for musicians to buy and sell the gear they use to create the music they love."}},"has_bounty?":true,"in_validation?":false,"rejected_anc_report_that_can_be_sent_back_to_anc_triagers?":false,"can_view_team":true,"can_view_report":true,"is_external_bug":false,"is_published":false,"is_participant":false,"has_collaborators":false,"stage":4,"public":true,"visibility":"full","cve_ids":[],"singular_disclosure_disabled":false,"disclosed_at":"2018-05-06T16:08:07.519Z","bug_reporter_agreed_on_going_public_at":"2018-04-06T16:07:46.422Z","team_member_agreed_on_going_public_at":null,"comments_closed?":false,"facebook_team?":false,"team_private?":false,"vulnerability_information":"# Description\nI found a Persistent XSS in a listing page. The flaw is in the SoundCloud link that the listing owner can attach(The parameter is called *product[soundcloud_link_attributes][link]*). There's no encoding on the user input and it looks like there's only client-side validation.\n\n# PoC\nThe payload:\n```\nhttps://soundcloud.com/rich-the-kid/sets/the-world-is-yours-15?fuzzing\" onload=alert(document.domain) x=\"\n```\nIf you try to put this payload straight into the \"Edit Listing\" page it'll give you the following error:\n```\nhttps://sandbox.reverb.com/listings/[YOUR_LISTING_ID]/edit\n```\n{F281627}\n\nBut it looks like there's only client side validation, when I tried to enter a valid link:\n```\nhttps://soundcloud.com/rich-the-kid/sets/the-world-is-yours-15\n```\nI got no error message(because it was a valid link)\nBut when I clicked \"Save \u0026 Review Listing\", intercepted the request and tampered the *product[soundcloud_link_attributes][link]* parameter's value to:\n```\nhttps://soundcloud.com/rich-the-kid/sets/the-world-is-yours-15?fuzzing\" onload=alert(document.domain) x=\"\n```\nIt updated successfully and because there's no encoding on this input parameter - it allowed me to inject javascript code that'll be stored on my listing page.\n{F281640}\n\nPoC Video: https://youtu.be/Y-8W422hLOw\n\n## Impact\n\nAn attacker can:\n* Perform a defacement on every possible store in the website (all he need is a single click from the victim)\n* Deny future access from any other shop owner that access this listing(with the self-PXSS that i reported 2 days ago: https://hackerone.com/reports/331725 )\n* Perform operations in the application on behalf of the victim\n\nThe hacker selected the **Cross-site Scripting (XSS) - Stored** weakness. This vulnerability type requires contextual information from the hacker. 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[ { "url": "https://api.github.com/repos/pandas-dev/pandas/issues/comments/250127581", "html_url": "https://github.com/pandas-dev/pandas/issues/14310#issuecomment-250127581", "issue_url": "https://api.github.com/repos/pandas-dev/pandas/issues/14310", "id": 250127581, "node_id": "MDEyOklzc3VlQ29tbWVudDI1MDEyNzU4MQ==", "user": { "login": "jreback", "id": 953992, "node_id": "MDQ6VXNlcjk1Mzk5Mg==", "avatar_url": "https://avatars2.githubusercontent.com/u/953992?v=4", "gravatar_id": "", "url": "https://api.github.com/users/jreback", "html_url": "https://github.com/jreback", "followers_url": "https://api.github.com/users/jreback/followers", "following_url": "https://api.github.com/users/jreback/following{/other_user}", "gists_url": "https://api.github.com/users/jreback/gists{/gist_id}", "starred_url": "https://api.github.com/users/jreback/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/jreback/subscriptions", "organizations_url": "https://api.github.com/users/jreback/orgs", "repos_url": "https://api.github.com/users/jreback/repos", "events_url": "https://api.github.com/users/jreback/events{/privacy}", "received_events_url": "https://api.github.com/users/jreback/received_events", "type": "User", "site_admin": false }, "created_at": "2016-09-28T10:14:55Z", "updated_at": "2016-09-28T10:14:55Z", "author_association": "CONTRIBUTOR", "body": "I guess. Why would this small difference actually matter in practice? If you are repeatedly using an indexer that is completely non-performant (in either case), and you should be indexing via a larger indexer.\n" }, { "url": "https://api.github.com/repos/pandas-dev/pandas/issues/comments/250127722", "html_url": "https://github.com/pandas-dev/pandas/issues/14310#issuecomment-250127722", "issue_url": "https://api.github.com/repos/pandas-dev/pandas/issues/14310", "id": 250127722, "node_id": "MDEyOklzc3VlQ29tbWVudDI1MDEyNzcyMg==", "user": { "login": "jreback", "id": 953992, "node_id": "MDQ6VXNlcjk1Mzk5Mg==", "avatar_url": "https://avatars2.githubusercontent.com/u/953992?v=4", "gravatar_id": "", "url": "https://api.github.com/users/jreback", "html_url": "https://github.com/jreback", "followers_url": "https://api.github.com/users/jreback/followers", "following_url": "https://api.github.com/users/jreback/following{/other_user}", "gists_url": "https://api.github.com/users/jreback/gists{/gist_id}", "starred_url": "https://api.github.com/users/jreback/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/jreback/subscriptions", "organizations_url": "https://api.github.com/users/jreback/orgs", "repos_url": "https://api.github.com/users/jreback/repos", "events_url": "https://api.github.com/users/jreback/events{/privacy}", "received_events_url": "https://api.github.com/users/jreback/received_events", "type": "User", "site_admin": false }, "created_at": "2016-09-28T10:15:41Z", "updated_at": "2016-09-28T10:15:41Z", "author_association": "CONTRIBUTOR", "body": "If you would like to investigate and see where / propose fix, then that would be great.\n" }, { "url": "https://api.github.com/repos/pandas-dev/pandas/issues/comments/326261169", "html_url": "https://github.com/pandas-dev/pandas/issues/14310#issuecomment-326261169", "issue_url": "https://api.github.com/repos/pandas-dev/pandas/issues/14310", "id": 326261169, "node_id": "MDEyOklzc3VlQ29tbWVudDMyNjI2MTE2OQ==", "user": { "login": "nesdis", "id": 17020932, "node_id": "MDQ6VXNlcjE3MDIwOTMy", "avatar_url": "https://avatars3.githubusercontent.com/u/17020932?v=4", "gravatar_id": "", "url": "https://api.github.com/users/nesdis", "html_url": "https://github.com/nesdis", "followers_url": "https://api.github.com/users/nesdis/followers", "following_url": "https://api.github.com/users/nesdis/following{/other_user}", "gists_url": "https://api.github.com/users/nesdis/gists{/gist_id}", "starred_url": "https://api.github.com/users/nesdis/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/nesdis/subscriptions", "organizations_url": "https://api.github.com/users/nesdis/orgs", "repos_url": "https://api.github.com/users/nesdis/repos", "events_url": "https://api.github.com/users/nesdis/events{/privacy}", "received_events_url": "https://api.github.com/users/nesdis/received_events", "type": "User", "site_admin": false }, "created_at": "2017-08-31T10:54:25Z", "updated_at": "2017-08-31T10:54:25Z", "author_association": "NONE", "body": "indexing of sparse dataframe looks to be slow because elements are being stored as multiple sparse series. It would be much faster if pandas stored the underlying elements as a coo_matrix instead, when all the columns are of the same datatype. @jreback Do you suppose sparse dataframe would benefit from this optimization?" }, { "url": "https://api.github.com/repos/pandas-dev/pandas/issues/comments/326624485", "html_url": "https://github.com/pandas-dev/pandas/issues/14310#issuecomment-326624485", "issue_url": "https://api.github.com/repos/pandas-dev/pandas/issues/14310", "id": 326624485, "node_id": "MDEyOklzc3VlQ29tbWVudDMyNjYyNDQ4NQ==", "user": { "login": "nesdis", "id": 17020932, "node_id": "MDQ6VXNlcjE3MDIwOTMy", "avatar_url": "https://avatars3.githubusercontent.com/u/17020932?v=4", "gravatar_id": "", "url": "https://api.github.com/users/nesdis", "html_url": "https://github.com/nesdis", "followers_url": "https://api.github.com/users/nesdis/followers", "following_url": "https://api.github.com/users/nesdis/following{/other_user}", "gists_url": "https://api.github.com/users/nesdis/gists{/gist_id}", "starred_url": "https://api.github.com/users/nesdis/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/nesdis/subscriptions", "organizations_url": "https://api.github.com/users/nesdis/orgs", "repos_url": "https://api.github.com/users/nesdis/repos", "events_url": "https://api.github.com/users/nesdis/events{/privacy}", "received_events_url": "https://api.github.com/users/nesdis/received_events", "type": "User", "site_admin": false }, "created_at": "2017-09-01T16:25:27Z", "updated_at": "2017-09-01T16:25:27Z", "author_association": "NONE", "body": "# python sparse dataframes are **ridiculously slow** when it comes to most operations vs sparse matrices:\r\n\r\n### Sparse matrix instantiation vs Sparse dataframe instantiation from numpy 2darray:\r\n\r\n```python\r\nd = numpy.zeros((10000,10000))\r\nd[1,2] = 3\r\n\r\ntimeit.timeit('m = coo_matrix(d)', globals=globals(), number=1)\r\n0.7182237296299819\r\n\r\ntimeit.timeit('df = pandas.DataFrame(d).to_sparse(0)', globals=globals(), number=1)\r\n206.5695096827077\r\n```\r\nSparse dataframe instantiation is about **280 times slower** vs sparse matrix\r\n\r\n### Sparse matrix slicing vs Sparse dataframe slicing\r\n\r\n```python\r\nr = m.tocsr()\r\ntimeit.timeit('r[:5,:].toarray()', globals=globals(), number=1)\r\n0.0005268476787705367\r\n\r\ntimeit.timeit('df.iloc[:5,:]', globals=globals(), number=1)\r\n\r\n'''\r\nMEMORY EXCEPTION!!\r\npython ended up consuming 6GB of my RAM\r\n'''\r\n```\r\n\r\nI dont understand why this bug is a duplicate of [Row slicing of a sparse dataframe is too slow #17408](https://github.com/pandas-dev/pandas/issues/17408)\r\n\r\n#14310 bug is about multi row indexing being slow. #17408 is about sparse dataframe being buggy and slow overall." }, { "url": "https://api.github.com/repos/pandas-dev/pandas/issues/comments/326625130", "html_url": "https://github.com/pandas-dev/pandas/issues/14310#issuecomment-326625130", "issue_url": "https://api.github.com/repos/pandas-dev/pandas/issues/14310", "id": 326625130, "node_id": "MDEyOklzc3VlQ29tbWVudDMyNjYyNTEzMA==", "user": { "login": "jreback", "id": 953992, "node_id": "MDQ6VXNlcjk1Mzk5Mg==", "avatar_url": "https://avatars2.githubusercontent.com/u/953992?v=4", "gravatar_id": "", "url": "https://api.github.com/users/jreback", "html_url": "https://github.com/jreback", "followers_url": "https://api.github.com/users/jreback/followers", "following_url": "https://api.github.com/users/jreback/following{/other_user}", "gists_url": "https://api.github.com/users/jreback/gists{/gist_id}", "starred_url": "https://api.github.com/users/jreback/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/jreback/subscriptions", "organizations_url": "https://api.github.com/users/jreback/orgs", "repos_url": "https://api.github.com/users/jreback/repos", "events_url": "https://api.github.com/users/jreback/events{/privacy}", "received_events_url": "https://api.github.com/users/jreback/received_events", "type": "User", "site_admin": false }, "created_at": "2017-09-01T16:28:17Z", "updated_at": "2017-09-01T16:28:17Z", "author_association": "CONTRIBUTOR", "body": "@nesdis you are welcome to have a look. However, virtually all support for sparse would have to be community driven. This is not really well supported, though @kernc has done a very nice job fixing some things up.\r\n\r\nDataFrames are column based so changing to internal data storage to coo would likely be a herculean task. If you need a numpy coo, simply use one. The usecases are different." }, { "url": "https://api.github.com/repos/pandas-dev/pandas/issues/comments/326628526", "html_url": "https://github.com/pandas-dev/pandas/issues/14310#issuecomment-326628526", "issue_url": "https://api.github.com/repos/pandas-dev/pandas/issues/14310", "id": 326628526, "node_id": "MDEyOklzc3VlQ29tbWVudDMyNjYyODUyNg==", "user": { "login": "nesdis", "id": 17020932, "node_id": "MDQ6VXNlcjE3MDIwOTMy", "avatar_url": "https://avatars3.githubusercontent.com/u/17020932?v=4", "gravatar_id": "", "url": "https://api.github.com/users/nesdis", "html_url": "https://github.com/nesdis", "followers_url": "https://api.github.com/users/nesdis/followers", "following_url": "https://api.github.com/users/nesdis/following{/other_user}", "gists_url": "https://api.github.com/users/nesdis/gists{/gist_id}", "starred_url": "https://api.github.com/users/nesdis/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/nesdis/subscriptions", "organizations_url": "https://api.github.com/users/nesdis/orgs", "repos_url": "https://api.github.com/users/nesdis/repos", "events_url": "https://api.github.com/users/nesdis/events{/privacy}", "received_events_url": "https://api.github.com/users/nesdis/received_events", "type": "User", "site_admin": false }, "created_at": "2017-09-01T16:42:28Z", "updated_at": "2017-09-01T16:42:28Z", "author_association": "NONE", "body": "@jreback can't the internal structure be changed only for the case of sparse-dataframe. The main advantage of a dataframe is the automatic reindexing and alignment based on labelled indexes for arithmetic operations. using coo means i am having to re-index and align manually for my arithmetics." }, { "url": "https://api.github.com/repos/pandas-dev/pandas/issues/comments/326630420", "html_url": "https://github.com/pandas-dev/pandas/issues/14310#issuecomment-326630420", "issue_url": "https://api.github.com/repos/pandas-dev/pandas/issues/14310", "id": 326630420, "node_id": "MDEyOklzc3VlQ29tbWVudDMyNjYzMDQyMA==", "user": { "login": "jreback", "id": 953992, "node_id": "MDQ6VXNlcjk1Mzk5Mg==", "avatar_url": "https://avatars2.githubusercontent.com/u/953992?v=4", "gravatar_id": "", "url": "https://api.github.com/users/jreback", "html_url": "https://github.com/jreback", "followers_url": "https://api.github.com/users/jreback/followers", "following_url": "https://api.github.com/users/jreback/following{/other_user}", "gists_url": "https://api.github.com/users/jreback/gists{/gist_id}", "starred_url": "https://api.github.com/users/jreback/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/jreback/subscriptions", "organizations_url": "https://api.github.com/users/jreback/orgs", "repos_url": "https://api.github.com/users/jreback/repos", "events_url": "https://api.github.com/users/jreback/events{/privacy}", "received_events_url": "https://api.github.com/users/jreback/received_events", "type": "User", "site_admin": false }, "created_at": "2017-09-01T16:50:16Z", "updated_at": "2017-09-01T16:50:16Z", "author_association": "CONTRIBUTOR", "body": "@nesdis the current design of pandas would make this quite difficult. In any event, I would suspect your issues are related to how you are indexing. Simply indexing by a list like a small number of times makes a slightly slower access pattern acceptable. Repeated indexing is an anti-pattern (IOW in a loop)." }, { "url": "https://api.github.com/repos/pandas-dev/pandas/issues/comments/326635327", "html_url": "https://github.com/pandas-dev/pandas/issues/14310#issuecomment-326635327", "issue_url": "https://api.github.com/repos/pandas-dev/pandas/issues/14310", "id": 326635327, "node_id": "MDEyOklzc3VlQ29tbWVudDMyNjYzNTMyNw==", "user": { "login": "nesdis", "id": 17020932, "node_id": "MDQ6VXNlcjE3MDIwOTMy", "avatar_url": "https://avatars3.githubusercontent.com/u/17020932?v=4", "gravatar_id": "", "url": "https://api.github.com/users/nesdis", "html_url": "https://github.com/nesdis", "followers_url": "https://api.github.com/users/nesdis/followers", "following_url": "https://api.github.com/users/nesdis/following{/other_user}", "gists_url": "https://api.github.com/users/nesdis/gists{/gist_id}", "starred_url": "https://api.github.com/users/nesdis/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/nesdis/subscriptions", "organizations_url": "https://api.github.com/users/nesdis/orgs", "repos_url": "https://api.github.com/users/nesdis/repos", "events_url": "https://api.github.com/users/nesdis/events{/privacy}", "received_events_url": "https://api.github.com/users/nesdis/received_events", "type": "User", "site_admin": false }, "created_at": "2017-09-01T17:12:07Z", "updated_at": "2017-09-01T17:12:07Z", "author_association": "NONE", "body": "@jreback I am not sure, but does pandas convert 2d numpy array (which is used to instantiate a dataframe) into multiple 1d arrays or refer to the array as a single 2d block? If it is the latter then treating the input data as a sparse 2d array block should be possible too? (instead of multiple 1d series/arrays).\r\n\r\nYes in my case my slicing is happening inside a for loop to get a subset of values, the sliced matrix/df is being multiplied with other matrices to generate probabilities for a subset of elements. At the moment I have not gotten rid of the loop." }, { "url": "https://api.github.com/repos/pandas-dev/pandas/issues/comments/326802053", "html_url": "https://github.com/pandas-dev/pandas/issues/14310#issuecomment-326802053", "issue_url": "https://api.github.com/repos/pandas-dev/pandas/issues/14310", "id": 326802053, "node_id": "MDEyOklzc3VlQ29tbWVudDMyNjgwMjA1Mw==", "user": { "login": "kernc", "id": 684364, "node_id": "MDQ6VXNlcjY4NDM2NA==", "avatar_url": "https://avatars2.githubusercontent.com/u/684364?v=4", "gravatar_id": "", "url": "https://api.github.com/users/kernc", "html_url": "https://github.com/kernc", "followers_url": "https://api.github.com/users/kernc/followers", "following_url": "https://api.github.com/users/kernc/following{/other_user}", "gists_url": "https://api.github.com/users/kernc/gists{/gist_id}", "starred_url": "https://api.github.com/users/kernc/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/kernc/subscriptions", "organizations_url": "https://api.github.com/users/kernc/orgs", "repos_url": "https://api.github.com/users/kernc/repos", "events_url": "https://api.github.com/users/kernc/events{/privacy}", "received_events_url": "https://api.github.com/users/kernc/received_events", "type": "User", "site_admin": false }, "created_at": "2017-09-03T12:31:45Z", "updated_at": "2017-09-03T12:31:45Z", "author_association": "CONTRIBUTOR", "body": "> It would be much faster if pandas stored the underlying elements as a coo_matrix instead, when all the columns are of the same datatype.\r\n\r\nImho not general enough. The case when all columns are of the same dtype is quite uncommon in the space of all possible columns/dtypes. What would probably work, however, is `SparseBlock` collecting all columns of the same dtype and no longer sharing the limitations of `NonConsolidatableMixIn`. One'd have to investigate. PRs are welcome.\r\n\r\n> Sparse dataframe instantiation is about **280 times slower** vs sparse matrix\r\n\r\nA better instantiation of SparseDataFrame would be via coo_matrix; just twice as slow:\r\n```py\r\n>>> %timeit coo_matrix(d)\r\n858 ms ± 2.67 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\r\n\r\n>>> %timeit pd.SparseDataFrame(coo_matrix(d))\r\n1.83 s ± 16.4 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\r\n```\r\n\r\n> does pandas convert 2d numpy array (which is used to instantiate a dataframe) into multiple 1d arrays\r\n\r\nYes, pandas is a column-oriented storage. Some columns are consolidated into a single 2d block of the same dtype, but not `SparseBlock`. https://github.com/pandas-dev/pandas/blob/870b6a6d6415c76d051b287adcb180ac3020b6e8/pandas/core/internals.py#L2606\r\n\r\nOptimize tight loops by converting first to a format with less overhead:\r\n```py\r\ncoo = sdf.to_coo()\r\n```" } ]
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{"textgrid.poem.62930": {"metadata": {"author": {"name": "Pfeffel, Gottlieb Konrad", "birth": "N.A.", "death": "N.A."}, "title": "1L: In einer Stra\u00dfe fand ein Knabe", "genre": "verse", "period": "N.A.", "pub_year": 1779, "urn": "N.A.", "language": ["de:0.99"], "booktitle": "N.A."}, "text": null, "poem": {"stanza.1": {"line.1": {"text": "In einer Stra\u00dfe fand ein Knabe", "tokens": ["In", "ei\u00b7ner", "Stra\u00b7\u00dfe", "fand", "ein", "Kna\u00b7be"], "token_info": ["word", "word", "word", "word", "word", "word"], "pos": ["APPR", "ART", "NN", "VVFIN", "ART", "NN"], "meter": "-+-+-+-+-", "measure": "iambic.tetra"}, "line.2": {"text": "Ein altes Goldst\u00fcck. Schaut doch her,", "tokens": ["Ein", "al\u00b7tes", "Gold\u00b7st\u00fcck", ".", "Schaut", "doch", "her", ","], "token_info": ["word", "word", "word", "punct", "word", "word", "word", "punct"], "pos": ["ART", "ADJA", "NN", "$.", "VVFIN", "ADV", "PTKVZ", "$,"], "meter": "-+-+-+-+", "measure": "iambic.tetra"}, "line.3": {"text": "Ihr Herrn, was ich gefunden habe!", "tokens": ["Ihr", "Herrn", ",", "was", "ich", "ge\u00b7fun\u00b7den", "ha\u00b7be", "!"], "token_info": ["word", "word", "punct", "word", "word", "word", "word", "punct"], "pos": ["PPOSAT", "NN", "$,", "PWS", "PPER", "VVPP", "VAFIN", "$."], "meter": "-+-+-+-+-", "measure": "iambic.tetra"}, "line.4": {"text": "Rief er entz\u00fcckt. Von ungef\u00e4hr", "tokens": ["Rief", "er", "ent\u00b7z\u00fcckt", ".", "Von", "un\u00b7ge\u00b7f\u00e4hr"], "token_info": ["word", "word", "word", "punct", "word", "word"], "pos": ["VVFIN", "PPER", "VVPP", "$.", "APPR", "ADJD"], "meter": "-+-+-+-+", "measure": "iambic.tetra"}, "line.5": {"text": "Sah es aus seiner Tr\u00f6delbude", "tokens": ["Sah", "es", "aus", "sei\u00b7ner", "Tr\u00f6\u00b7del\u00b7bu\u00b7de"], "token_info": ["word", "word", "word", "word", "word"], "pos": ["VVFIN", "PPER", "APPR", "PPOSAT", "NN"], "meter": "-+-+-+-+-", "measure": "iambic.tetra"}, "line.6": {"text": "Ein Rabbi, Namens Ephraim:", "tokens": ["Ein", "Rab\u00b7bi", ",", "Na\u00b7mens", "Eph\u00b7raim", ":"], "token_info": ["word", "word", "punct", "word", "word", "punct"], "pos": ["ART", "NN", "$,", "NN", "NE", "$."], "meter": "-+--+-+", "measure": "iambic.tri.relaxed"}, "line.7": {"text": "Bey meiner Schomme, bl\u00f6ckt der Jude", "tokens": ["Bey", "mei\u00b7ner", "Schom\u00b7me", ",", "bl\u00f6ckt", "der", "Ju\u00b7de"], "token_info": ["word", "word", "word", "punct", "word", "word", "word"], "pos": ["APPR", "PPOSAT", "NN", "$,", "VVFIN", "ART", "NN"], "meter": "-+-+-+-+-", "measure": "iambic.tetra"}, "line.8": {"text": "Und l\u00e4chelt Hohn und stillen Grimm,", "tokens": ["Und", "l\u00e4\u00b7chelt", "Hohn", "und", "stil\u00b7len", "Grimm", ","], "token_info": ["word", "word", "word", "word", "word", "word", "punct"], "pos": ["KON", "VVFIN", "NN", "KON", "VVFIN", "NE", "$,"], "meter": "-+-+-+-+", "measure": "iambic.tetra"}, "line.9": {"text": "Das Ding ist falsch! Dem armen Knaben", "tokens": ["Das", "Ding", "ist", "falsch", "!", "Dem", "ar\u00b7men", "Kna\u00b7ben"], "token_info": ["word", "word", "word", "word", "punct", "word", "word", "word"], "pos": ["ART", "NN", "VAFIN", "ADJD", "$.", "ART", "ADJA", "NN"], "meter": "-+-+-+-+-", "measure": "iambic.tetra"}, "line.10": {"text": "Wars nun auf einmal bang ums Herz.", "tokens": ["Wars", "nun", "auf", "ein\u00b7mal", "bang", "ums", "Herz", "."], "token_info": ["word", "word", "word", "word", "word", "word", "word", "punct"], "pos": ["VAFIN", "ADV", "APPR", "ADV", "ADJD", "APPRART", "NN", "$."], "meter": "-+-+-+-+", "measure": "iambic.tetra"}, "line.11": {"text": "Ein wenig Zusatz mocht es haben,", "tokens": ["Ein", "we\u00b7nig", "Zu\u00b7satz", "mocht", "es", "ha\u00b7ben", ","], "token_info": ["word", "word", "word", "word", "word", "word", "punct"], "pos": ["ART", "PIAT", "NN", "VVFIN", "PPER", "VAFIN", "$,"], "meter": "-+-+-+-+-", "measure": "iambic.tetra"}, "line.12": {"text": "Doch war es Gold. Der bittre Scherz,", "tokens": ["Doch", "war", "es", "Gold", ".", "Der", "bitt\u00b7re", "Scherz", ","], "token_info": ["word", "word", "word", "word", "punct", "word", "word", "word", "punct"], "pos": ["KON", "VAFIN", "PPER", "NN", "$.", "ART", "ADJA", "NN", "$,"], "meter": "-+-+-+-+", "measure": "iambic.tetra"}, "line.13": {"text": "Die schlaue Logik des Sophisten", "tokens": ["Die", "schlau\u00b7e", "Lo\u00b7gik", "des", "So\u00b7phis\u00b7ten"], "token_info": ["word", "word", "word", "word", "word"], "pos": ["ART", "ADJA", "NN", "ART", "NN"], "meter": "-+--+--+-", "measure": "amphibrach.tri"}, "line.14": {"text": "Schwieg nicht, bis er voll Aergerni\u00df", "tokens": ["Schwieg", "nicht", ",", "bis", "er", "voll", "A\u00b7er\u00b7ger\u00b7ni\u00df"], "token_info": ["word", "word", "punct", "word", "word", "word", "word"], "pos": ["NN", "PTKNEG", "$,", "KOUS", "PPER", "ADJD", "NN"], "meter": "--+--+-+-", "measure": "anapaest.di.plus"}, "line.15": {"text": "Das St\u00fcck in einen Brunnen schmi\u00df.", "tokens": ["Das", "St\u00fcck", "in", "ei\u00b7nen", "Brun\u00b7nen", "schmi\u00df", "."], "token_info": ["word", "word", "word", "word", "word", "word", "punct"], "pos": ["ART", "NN", "APPR", "ART", "NN", "VVFIN", "$."], "meter": "-+-+-+-+", "measure": "iambic.tetra"}}, "stanza.2": {"line.1": {"text": "Ihr unberufnen Exorcisten", "tokens": ["Ihr", "un\u00b7be\u00b7ruf\u00b7nen", "Ex\u00b7or\u00b7cis\u00b7ten"], "token_info": ["word", "word", "word"], "pos": ["PPOSAT", "ADJA", "NN"], "meter": "-+-+-+-+-", "measure": "iambic.tetra"}, "line.2": {"text": "Des Glaubens! Dieser harte Mann", "tokens": ["Des", "Glau\u00b7bens", "!", "Die\u00b7ser", "har\u00b7te", "Mann"], "token_info": ["word", "word", "punct", "word", "word", "word"], "pos": ["ART", "NN", "$.", "PDAT", "ADJA", "NN"], "meter": "-+-+-+-+", "measure": "iambic.tetra"}, "line.3": {"text": "Ist euer Bild: ihr raubt dem Christen", "tokens": ["Ist", "eu\u00b7er", "Bild", ":", "ihr", "raubt", "dem", "Chris\u00b7ten"], "token_info": ["word", "word", "word", "punct", "word", "word", "word", "word"], "pos": ["VAFIN", "PPOSAT", "NN", "$.", "PPER", "VVFIN", "ART", "NN"], "meter": "-+-+-+-+-", "measure": "iambic.tetra"}, "line.4": {"text": "Ein Gut, das euch nicht nutzen kann.", "tokens": ["Ein", "Gut", ",", "das", "euch", "nicht", "nut\u00b7zen", "kann", "."], "token_info": ["word", "word", "punct", "word", "word", "word", "word", "word", "punct"], "pos": ["ART", "NN", "$,", "PRELS", "PPER", "PTKNEG", "VVINF", "VMFIN", "$."], "meter": "-+-+-+-+", "measure": "iambic.tetra"}, "line.5": {"text": "Gelahrte Herrn Fragmentenschreiber,", "tokens": ["Ge\u00b7lahr\u00b7te", "Herrn", "Frag\u00b7men\u00b7ten\u00b7schrei\u00b7ber", ","], "token_info": ["word", "word", "word", "punct"], "pos": ["ADJA", "NN", "NE", "$,"], "meter": "-+--+--+-", "measure": "amphibrach.tri"}, "line.6": {"text": "O werdet lieber Stra\u00dfenr\u00e4uber.", "tokens": ["O", "wer\u00b7det", "lie\u00b7ber", "Stra\u00b7\u00dfen\u00b7r\u00e4u\u00b7ber", "."], "token_info": ["word", "word", "word", "word", "punct"], "pos": ["NE", "VAFIN", "ADV", "NN", "$."], "meter": "-+-+-+-+-", "measure": "iambic.tetra"}}, "stanza.3": {"line.1": {"text": "In einer Stra\u00dfe fand ein Knabe", "tokens": ["In", "ei\u00b7ner", "Stra\u00b7\u00dfe", "fand", "ein", "Kna\u00b7be"], "token_info": ["word", "word", "word", "word", "word", "word"], "pos": ["APPR", "ART", "NN", "VVFIN", "ART", "NN"], "meter": "-+-+-+-+-", "measure": "iambic.tetra"}, "line.2": {"text": "Ein altes Goldst\u00fcck. Schaut doch her,", "tokens": ["Ein", "al\u00b7tes", "Gold\u00b7st\u00fcck", ".", "Schaut", "doch", "her", ","], "token_info": ["word", "word", "word", "punct", "word", "word", "word", "punct"], "pos": ["ART", "ADJA", "NN", "$.", "VVFIN", "ADV", "PTKVZ", "$,"], "meter": "-+-+-+-+", "measure": "iambic.tetra"}, "line.3": {"text": "Ihr Herrn, was ich gefunden habe!", "tokens": ["Ihr", "Herrn", ",", "was", "ich", "ge\u00b7fun\u00b7den", "ha\u00b7be", "!"], "token_info": ["word", "word", "punct", "word", "word", "word", "word", "punct"], "pos": ["PPOSAT", "NN", "$,", "PWS", "PPER", "VVPP", "VAFIN", "$."], "meter": "-+-+-+-+-", "measure": "iambic.tetra"}, "line.4": {"text": "Rief er entz\u00fcckt. Von ungef\u00e4hr", "tokens": ["Rief", "er", "ent\u00b7z\u00fcckt", ".", "Von", "un\u00b7ge\u00b7f\u00e4hr"], "token_info": ["word", "word", "word", "punct", "word", "word"], "pos": ["VVFIN", "PPER", "VVPP", "$.", "APPR", "ADJD"], "meter": "-+-+-+-+", "measure": "iambic.tetra"}, "line.5": {"text": "Sah es aus seiner Tr\u00f6delbude", "tokens": ["Sah", "es", "aus", "sei\u00b7ner", "Tr\u00f6\u00b7del\u00b7bu\u00b7de"], "token_info": ["word", "word", "word", "word", "word"], "pos": ["VVFIN", "PPER", "APPR", "PPOSAT", "NN"], "meter": "-+-+-+-+-", "measure": "iambic.tetra"}, "line.6": {"text": "Ein Rabbi, Namens Ephraim:", "tokens": ["Ein", "Rab\u00b7bi", ",", "Na\u00b7mens", "Eph\u00b7raim", ":"], "token_info": ["word", "word", "punct", "word", "word", "punct"], "pos": ["ART", "NN", "$,", "NN", "NE", "$."], "meter": "-+--+-+", "measure": "iambic.tri.relaxed"}, "line.7": {"text": "Bey meiner Schomme, bl\u00f6ckt der Jude", "tokens": ["Bey", "mei\u00b7ner", "Schom\u00b7me", ",", "bl\u00f6ckt", "der", "Ju\u00b7de"], "token_info": ["word", "word", "word", "punct", "word", "word", "word"], "pos": ["APPR", "PPOSAT", "NN", "$,", "VVFIN", "ART", "NN"], "meter": "-+-+-+-+-", "measure": "iambic.tetra"}, "line.8": {"text": "Und l\u00e4chelt Hohn und stillen Grimm,", "tokens": ["Und", "l\u00e4\u00b7chelt", "Hohn", "und", "stil\u00b7len", "Grimm", ","], "token_info": ["word", "word", "word", "word", "word", "word", "punct"], "pos": ["KON", "VVFIN", "NN", "KON", "VVFIN", "NE", "$,"], "meter": "-+-+-+-+", "measure": "iambic.tetra"}, "line.9": {"text": "Das Ding ist falsch! Dem armen Knaben", "tokens": ["Das", "Ding", "ist", "falsch", "!", "Dem", "ar\u00b7men", "Kna\u00b7ben"], "token_info": ["word", "word", "word", "word", "punct", "word", "word", "word"], "pos": ["ART", "NN", "VAFIN", "ADJD", "$.", "ART", "ADJA", "NN"], "meter": "-+-+-+-+-", "measure": "iambic.tetra"}, "line.10": {"text": "Wars nun auf einmal bang ums Herz.", "tokens": ["Wars", "nun", "auf", "ein\u00b7mal", "bang", "ums", "Herz", "."], "token_info": ["word", "word", "word", "word", "word", "word", "word", "punct"], "pos": ["VAFIN", "ADV", "APPR", "ADV", "ADJD", "APPRART", "NN", "$."], "meter": "-+-+-+-+", "measure": "iambic.tetra"}, "line.11": {"text": "Ein wenig Zusatz mocht es haben,", "tokens": ["Ein", "we\u00b7nig", "Zu\u00b7satz", "mocht", "es", "ha\u00b7ben", ","], "token_info": ["word", "word", "word", "word", "word", "word", "punct"], "pos": ["ART", "PIAT", "NN", "VVFIN", "PPER", "VAFIN", "$,"], "meter": "-+-+-+-+-", "measure": "iambic.tetra"}, "line.12": {"text": "Doch war es Gold. Der bittre Scherz,", "tokens": ["Doch", "war", "es", "Gold", ".", "Der", "bitt\u00b7re", "Scherz", ","], "token_info": ["word", "word", "word", "word", "punct", "word", "word", "word", "punct"], "pos": ["KON", "VAFIN", "PPER", "NN", "$.", "ART", "ADJA", "NN", "$,"], "meter": "-+-+-+-+", "measure": "iambic.tetra"}, "line.13": {"text": "Die schlaue Logik des Sophisten", "tokens": ["Die", "schlau\u00b7e", "Lo\u00b7gik", "des", "So\u00b7phis\u00b7ten"], "token_info": ["word", "word", "word", "word", "word"], "pos": ["ART", "ADJA", "NN", "ART", "NN"], "meter": "-+--+--+-", "measure": "amphibrach.tri"}, "line.14": {"text": "Schwieg nicht, bis er voll Aergerni\u00df", "tokens": ["Schwieg", "nicht", ",", "bis", "er", "voll", "A\u00b7er\u00b7ger\u00b7ni\u00df"], "token_info": ["word", "word", "punct", "word", "word", "word", "word"], "pos": ["NN", "PTKNEG", "$,", "KOUS", "PPER", "ADJD", "NN"], "meter": "--+--+-+-", "measure": "anapaest.di.plus"}, "line.15": {"text": "Das St\u00fcck in einen Brunnen schmi\u00df.", "tokens": ["Das", "St\u00fcck", "in", "ei\u00b7nen", "Brun\u00b7nen", "schmi\u00df", "."], "token_info": ["word", "word", "word", "word", "word", "word", "punct"], "pos": ["ART", "NN", "APPR", "ART", "NN", "VVFIN", "$."], "meter": "-+-+-+-+", "measure": "iambic.tetra"}}, "stanza.4": {"line.1": {"text": "Ihr unberufnen Exorcisten", "tokens": ["Ihr", "un\u00b7be\u00b7ruf\u00b7nen", "Ex\u00b7or\u00b7cis\u00b7ten"], "token_info": ["word", "word", "word"], "pos": ["PPOSAT", "ADJA", "NN"], "meter": "-+-+-+-+-", "measure": "iambic.tetra"}, "line.2": {"text": "Des Glaubens! Dieser harte Mann", "tokens": ["Des", "Glau\u00b7bens", "!", "Die\u00b7ser", "har\u00b7te", "Mann"], "token_info": ["word", "word", "punct", "word", "word", "word"], "pos": ["ART", "NN", "$.", "PDAT", "ADJA", "NN"], "meter": "-+-+-+-+", "measure": "iambic.tetra"}, "line.3": {"text": "Ist euer Bild: ihr raubt dem Christen", "tokens": ["Ist", "eu\u00b7er", "Bild", ":", "ihr", "raubt", "dem", "Chris\u00b7ten"], "token_info": ["word", "word", "word", "punct", "word", "word", "word", "word"], "pos": ["VAFIN", "PPOSAT", "NN", "$.", "PPER", "VVFIN", "ART", "NN"], "meter": "-+-+-+-+-", "measure": "iambic.tetra"}, "line.4": {"text": "Ein Gut, das euch nicht nutzen kann.", "tokens": ["Ein", "Gut", ",", "das", "euch", "nicht", "nut\u00b7zen", "kann", "."], "token_info": ["word", "word", "punct", "word", "word", "word", "word", "word", "punct"], "pos": ["ART", "NN", "$,", "PRELS", "PPER", "PTKNEG", "VVINF", "VMFIN", "$."], "meter": "-+-+-+-+", "measure": "iambic.tetra"}, "line.5": {"text": "Gelahrte Herrn Fragmentenschreiber,", "tokens": ["Ge\u00b7lahr\u00b7te", "Herrn", "Frag\u00b7men\u00b7ten\u00b7schrei\u00b7ber", ","], "token_info": ["word", "word", "word", "punct"], "pos": ["ADJA", "NN", "NE", "$,"], "meter": "-+--+--+-", "measure": "amphibrach.tri"}, "line.6": {"text": "O werdet lieber Stra\u00dfenr\u00e4uber.", "tokens": ["O", "wer\u00b7det", "lie\u00b7ber", "Stra\u00b7\u00dfen\u00b7r\u00e4u\u00b7ber", "."], "token_info": ["word", "word", "word", "word", "punct"], "pos": ["NE", "VAFIN", "ADV", "NN", "$."], "meter": "-+-+-+-+-", "measure": "iambic.tetra"}}}}}
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{"definitions": [{"wordtype": "Noun", "description": "Half a poetic verse or line, or a verse or line not completed."}]}
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{ "actions": [ { "acted_at": "2007-05-02", "committee": "Committee on Armed Services", "references": [], "status": "REFERRED", "text": "Read twice and referred to the Committee on Armed Services.", "type": "referral" } ], "amendments": [], "bill_id": "s1272-110", "bill_type": "s", "committees": [ { "activity": [ "referral", "in committee" ], "committee": "Senate Armed Services", "committee_id": "SSAS" } ], "congress": "110", "cosponsors": [ { "district": null, "name": "Coleman, Norm", "sponsored_at": "2007-05-02", "state": "MN", "thomas_id": "01697", "title": "Sen", "withdrawn_at": null }, { "district": null, "name": "Isakson, Johnny", "sponsored_at": "2007-05-02", "state": "GA", "thomas_id": "01608", "title": "Sen", "withdrawn_at": null }, { "district": null, "name": "Klobuchar, Amy", "sponsored_at": "2007-05-02", "state": "MN", "thomas_id": "01826", "title": "Sen", "withdrawn_at": null }, { "district": null, "name": "Lincoln, Blanche L.", "sponsored_at": "2007-12-06", "state": "AR", "thomas_id": "01570", "title": "Sen", "withdrawn_at": null } ], "enacted_as": null, "history": { "awaiting_signature": false, "enacted": false, "vetoed": false }, "introduced_at": "2007-05-02", "number": "1272", "official_title": "A bill to establish the National Guard Yellow Ribbon Reintegration Program.", "popular_title": null, "related_bills": [ { "bill_id": "hr2090-110", "reason": "identical" } ], "short_title": "Yellow Ribbon Reintegration Program Act of 2007", "sponsor": { "district": null, "name": "Chambliss, Saxby", "state": "GA", "thomas_id": "00188", "title": "Sen", "type": "person" }, "status": "REFERRED", "status_at": "2007-05-02", "subjects": [ "Armed forces and national security", "Families", "Federal advisory bodies", "Government operations and politics", "Government publicity", "Labor and employment", "Military dependents", "National Guard", "Veterans' benefits", "Veterans' employment" ], "subjects_top_term": "Armed forces and national security", "summary": { "as": "Introduced", "date": "2007-05-02", "text": "Yellow Ribbon Reintegration Program Act of 2007 - Directs the Secretary of Defense to establish a national combat veteran reintegration program (to be known as the Yellow Ribbon Reintegration Program) to provide National Guard members and their families with information, services, referral, and outreach opportunities throughout the entire deployment cycle. Requires the Program to consist of informational events and activities for such members, their families, and community members through the following phases of the deployment cycle: (1) pre-deployment; (2) deployment; (3) demobilization; and (4) post-deployment-reconstitution. Requires the: (1) National Guard Bureau to establish the Office for Reintegration Programs to administer state National Guard reintegration programs; and (2) Bureau Chief to establish a Center for Excellence in Reintegration." }, "titles": [ { "as": "introduced", "title": "Yellow Ribbon Reintegration Program Act of 2007", "type": "short" }, { "as": "introduced", "title": "A bill to establish the National Guard Yellow Ribbon Reintegration Program.", "type": "official" } ], "updated_at": "2013-02-02T20:43:33-05:00" }
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{ "url": "http://www.nytimes.com/2007/07/22/fashion/22love.html", "headline": "The House of No Personal Pronouns", "dateline": { "year": 2007, "month": 7, "day": 22 }, "byline": "Ada Brunstein", "text": "MY toothbrush is one of four standing upright in a cup on the bathroom sink. Four toothbrushes in a cup — the very image of domesticity, of family life. But our cup contains a different kind of domesticity. These toothbrushes belong to me, my boyfriend, his wife and her lover.\n\nI try to keep mine separate, encasing it in a white plastic toothbrush holder so it won’t touch the other bristles. So it won’t touch her bristles. The other toothbrushes stand free, liberated. Sometimes it seems as if I’m the only one troubled by this arrangement.\n\nAt the start, I didn’t think I would be. The separation of my boyfriend and his wife had been explained to me in all of its maddening reasonableness. There had been no betrayals, no angry words, no slammed doors. They had tried counseling. But after seven years, they thought there was nothing left to do but move on and move out.\n\nProblem is, they moved on but didn’t move out. Both have modest incomes, so she couldn’t afford his share of the house, which is in a costly area. They had bought it only two years before, and he didn’t want to sell it. So they moved to separate bedrooms and agreed to share custody of their cat.\n\n Some months later, they each took up with new partners, the wife’s boyfriend and me, in the same week. Which precipitated the following arrangement: When the wife and her man are at the house, her husband and I stay at my place. When they’re at her boyfriend’s place, we stay at the house. \n\nDivorce is supposedly somewhere on the horizon. Meanwhile, the four of us have been living this way for almost a year. \n\nAt first I liked the edginess of it all. I considered it a personal challenge. In the past, my jealousies had gotten the better of me. I once argued with a boyfriend over whether I would be O.K. with him sleeping with Uma Thurman (should he ever have the chance). Two months later she showed up in a bar we frequented in the West Village and the argument started all over again.\n\nThat was the old me. This was going to be the new me. A stronger, cooler, nothing-fazes-me sort of girlfriend who would prove I’ve outgrown the formerly jealous me. I would be unconventional, brave, hip and oh-so-bohemian in my nonchalance. \n\nI had met him at work several years before. He is a philosopher, a whirlwind of ifs and thens, of rights and wrongs, an analytical vortex, examining every truth and assumption. I was instantly drawn to him. But he was taken and I found someone else. We met only in groups at work outings and in bars. We were part of the same office book club. We had an office-appropriate friendship of sorts. But the intrigue remained.\n\nI was curious about his wife as well. What kind of woman — not which woman — but what kind of woman would be his wife? When I was out I would look for her. Once I imagined she was a petite brunette with a quick step and a purposeless smile walking past me on the street. Another time I wondered if she was the naked dancer midleap on the cover of a local calendar. I wanted to get inside her head. Now I’ve been inside her house every week for a year.\n\nThere has been a lot to negotiate. I had to establish some ground rules. No more late-night cellphone calls from her just to check in. Done (after a few months). No weekend visits by him to her family’s house to perpetuate the marital-bliss myth. Done (after the fact). \n\nThere also have been linguistic negotiations. He has adopted the passive voice to make it easier on me. I once stood in front of a bookcase in the kitchen, three shelves of which hold an impressive collection of salt and pepper shakers from across the country.\n\n“You collect salt and pepper shakers?” I asked. \n\n“There are salt and pepper shakers that have come into the house over the years,” he said. \n\nAnd he has been more careful with possessives. “The house,” he says, not “our house.” \n\nShe and I have met several times and are cordial, maybe friendly. At one point she even allowed me to interview her for a documentary project I was working on. But the bulk of our relationship is silent, conducted in isolation, and involves a kind of uniquely female warfare.\n\nWOMEN don’t wage war the way men wage war, not at first, not unless there’s no other way. Men wage war in the open plains and deserts, donning full body armor, lugging lethal weapons. Women wage battles so imperceptibly that it’s not always clear there’s a battle at all, like tremors in the earth that you can’t quite feel, but you may notice the wind is suddenly odd or the animals are acting funny. \n\nAt first I thought she was just messy. Her shoes are always thrown around the house, one pair in the hallway, one pair in the kitchen, one in the living room under the coffee table where my feet may rest. But they’re shoes, after all — where else would she put them but on the floor?\n\nThen there are the magazines. Back issues of Us, People and Vanity Fair tossed onto every counter and tabletop. I can’t put anything on any surface without having to move something of hers aside. But how could I mind, really? I read those magazines on occasion. I can appreciate having them at my disposal without having to pay for them. I leaf through them now and then, noticing earmarked pages and wondering what it was on those pages that drew her attention. \n\nI buy my own magazines and try to coordinate with hers. Sometimes it’s Marie Claire, sometimes Cosmo. Sometimes Uma is on the cover and I laugh at my former self, even as I find myself reverting to that self. What she doesn’t have lying around, I bring in and add to the piles. My magazines sometimes end up buried under hers, but when that happens I do my own bit of rearranging and set mine back on top. \n\nMore irksome is the clothing she leaves around: the socks under the toilet and the burgundy bra she left drying on the radiator in the bathroom, cups pointed up. Now and then an image of my boyfriend’s wife’s breasts pops into my mind because of that bra. \n\nBut apparently the bra and its side effects weren’t enough. A week later, she left her full-length Japanese dress dangling precariously from a hanger in the kitchen doorway for a full week while she was away. \n\nNormally I don’t talk to him about these things. Men don’t understand this kind of battle. But this time I asked him why she might have hung the dress in the doorway of the most used room in the house, and he said, “She didn’t want to wrinkle it, I guess.”\n\n“Doesn’t she have her own room for these things?” I asked.\n\n“I guess there was no space,” he said. Worse, he seemed to believe it. \n\nEvery time I entered the kitchen that week, I brushed close to the dress. It was hard to squeak by without touching it, but still I made a special effort. Sometimes it swung, but it hung on. \n\nAs the week went on, I was more careless, which is to say I was more careful, deliberate. When I passed by, my arm swept across it. I backed into it with a well-crafted absent-mindedness. I wanted to knock the thing down to the ground, to accidentally tread on it, to trip on it even. Maybe I’d twist my ankle on her long silk dress that I couldn’t help but knock down because what was it doing in the doorway of the kitchen anyway where it was in everyone’s way? \n\nBut the thing never fell, and for a week a full-length reminder of her body hung from the kitchen doorway.\n\nI HAVE a confession to make. I have since started knocking things off tables and countertops. Her sunglasses, her lip gloss, hairpins. These are my small protests, my attempts to disrupt her comfort, to dislodge her, perhaps. I imagine her looking for the missing items and finding them mysteriously scattered under chairs and couches. If suspicions arise, I can always say the cat must have done it. \n\nMeanwhile, she has started a home makeover, installing a decorative light-switch cover just outside his bedroom and buying a new couch, a mirror and other random items. A few weeks ago she painted the hallway. Does she mean to lay claim to her place while putting me in mine?\n\nHer latest addition, a fake yellow canary that she affixed to the front door, simply can’t be ignored. With any luck, the cat will soon mistake the curio for a real bird and that will be the end of it.\n\nAnd amid these tremors, imperceptible to most, the animal started acting funny.\n\nI don’t blame him; cats are territorial, and his territory is constantly in flux. Attempting to keep up with the rotating occupancy, he sleeps in her bed when she and her boyfriend are in the house, and when we’re in residence he sleeps with us. \n\nBut while husband and wife talk daily to coordinate schedules, and each, in turn, informs the boyfriend and me, no one consults the cat, who never knows from one night to the next who will be in the house or which bed he’ll sleep in. \n\nFor a long time he was agitated, racing back and forth and all around the house and languishing between the various rooms, half his body in one, half in another. He meowed incessantly. Until one night he peed on the wife’s bed, and then the next night peed on my boyfriend’s bed, claiming both as his own. He has been fine ever since.\n\nI wish the rest of us could find so easy a fix." }
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{"dta.poem.2925": {"metadata": {"author": {"name": "R\u00fcckert, Friedrich", "birth": "N.A.", "death": "N.A."}, "title": "124.", "genre": "Lyrik", "period": "N.A.", "pub_year": "1838", "urn": "urn:nbn:de:kobv:b4-200905195108", "language": ["de:0.99"], "booktitle": "N.A."}, "poem": {"stanza.1": {"line.1": {"text": "Wei\u00dft du, was Liebe sei? Da\u00df eine dir gefallen,", "tokens": ["Wei\u00dft", "du", ",", "was", "Lie\u00b7be", "sei", "?", "Da\u00df", "ei\u00b7ne", "dir", "ge\u00b7fal\u00b7len", ","], "token_info": ["word", "word", "punct", "word", "word", "word", "punct", "word", "word", "word", "word", "punct"], "pos": ["VVFIN", "PPER", "$,", "PWS", "NN", "VAFIN", "$.", "KOUS", "ART", "PPER", "VVPP", "$,"], "meter": "-+-+-+-+-+-+-", "measure": "alexandrine.iambic.hexa"}, "line.2": {"text": "Ists nicht, auch das nicht, da\u00df sie dir gefiel vor allen.", "tokens": ["Ists", "nicht", ",", "auch", "das", "nicht", ",", "da\u00df", "sie", "dir", "ge\u00b7fiel", "vor", "al\u00b7len", "."], "token_info": ["word", "word", "punct", "word", "word", "word", "punct", "word", "word", "word", "word", "word", "word", "punct"], "pos": ["NE", "PTKNEG", "$,", "ADV", "PDS", "PTKNEG", "$,", "KOUS", "PPER", "PPER", "VVFIN", "APPR", "PIAT", "$."], "meter": "-+-+-+-+-+-+-", "measure": "alexandrine.iambic.hexa"}}, "stanza.2": {"line.1": {"text": "Doch andere zu sehn, und sch\u00f6ner sie zu finden,", "tokens": ["Doch", "an\u00b7de\u00b7re", "zu", "sehn", ",", "und", "sch\u00f6\u00b7ner", "sie", "zu", "fin\u00b7den", ","], "token_info": ["word", "word", "word", "word", "punct", "word", "word", "word", "word", "word", "punct"], "pos": ["KON", "PIS", "PTKZU", "VVINF", "$,", "KON", "ADJA", "PPER", "PTKZU", "VVINF", "$,"], "meter": "-+-+-+-+-+-+-", "measure": "alexandrine.iambic.hexa"}, "line.2": {"text": "Geistreicher auch, und doch nicht Lust noch Neid empfinden,", "tokens": ["Geist\u00b7rei\u00b7cher", "auch", ",", "und", "doch", "nicht", "Lust", "noch", "Neid", "emp\u00b7fin\u00b7den", ","], "token_info": ["word", "word", "punct", "word", "word", "word", "word", "word", "word", "word", "punct"], "pos": ["NN", "ADV", "$,", "KON", "ADV", "PTKNEG", "NN", "ADV", "NN", "VVFIN", "$,"], "meter": "-+-+-+-+-+-+-", "measure": "alexandrine.iambic.hexa"}}, "stanza.3": {"line.1": {"text": "Und f\u00fchlen, da\u00df es nur zur Einen hin dich zieht;", "tokens": ["Und", "f\u00fch\u00b7len", ",", "da\u00df", "es", "nur", "zur", "Ei\u00b7nen", "hin", "dich", "zieht", ";"], "token_info": ["word", "word", "punct", "word", "word", "word", "word", "word", "word", "word", "word", "punct"], "pos": ["KON", "VVFIN", "$,", "KOUS", "PPER", "ADV", "APPRART", "ART", "ADV", "PPER", "VVFIN", "$."], "meter": "-+-+-+-+-+-+", "measure": "alexandrine.iambic.hexa"}, "line.2": {"text": "Die Lieb' ist das, die f\u00fchlt, nicht denket oder sieht.", "tokens": ["Die", "Lieb'", "ist", "das", ",", "die", "f\u00fchlt", ",", "nicht", "den\u00b7ket", "o\u00b7der", "sieht", "."], "token_info": ["word", "word", "word", "word", "punct", "word", "word", "punct", "word", "word", "word", "word", "punct"], "pos": ["ART", "NN", "VAFIN", "PDS", "$,", "PRELS", "VVFIN", "$,", "PTKNEG", "VVFIN", "KON", "VVFIN", "$."], "meter": "-+-+-+-+-+-+", "measure": "alexandrine.iambic.hexa"}}}}}
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{"651380":{"success":true,"data":{"type":"game","name":"BANG! BANG! Totally Accurate Redneck Simulator","steam_appid":651380,"required_age":0,"is_free":false,"detailed_description":"BANG! BANG! Totally Accurate Redneck Simulator is simple, silly and very addictive \u2013 thanks mainly due to its drunken control scheme that makes the simple task of shooting a few bottles very hard indeed. In the game you play a lone gunman who\u2019s had a little too much to drink. So what better way to prove your sobriety than to pull out a couple of guns and start shooting targets?<br \/>\r\n<br \/>\r\nYour goal is to shoot all the blue bottles on each level. You aim your guns with the mouse, but due to your inebriation your gun hand is very shaky. This means that even if you line up the shot perfectly with the mouse then your drunken aim could make the bullet go anywhere, with ricochets causing lots of physics based destruction and often causing you to accidentally (and hilariously) shoot yourself. Your wonky aim can make even simple shots hard to hit, and as you progress through the levels things get even harder, with you having to pull of trick shots to hit the targets.<br \/>\r\n<br \/>\r\nThe super hard difficulty could make Bang! Bang! a frustrating experience, but thankfully even missed shots are a joy to behold thanks to its fun sense of humour, quick restarts and chaotic physics based carnage caused by your shooting. Well worth checking out for some super silly drunken shooter action.","about_the_game":"BANG! BANG! Totally Accurate Redneck Simulator is simple, silly and very addictive \u2013 thanks mainly due to its drunken control scheme that makes the simple task of shooting a few bottles very hard indeed. In the game you play a lone gunman who\u2019s had a little too much to drink. So what better way to prove your sobriety than to pull out a couple of guns and start shooting targets?<br \/>\r\n<br \/>\r\nYour goal is to shoot all the blue bottles on each level. You aim your guns with the mouse, but due to your inebriation your gun hand is very shaky. This means that even if you line up the shot perfectly with the mouse then your drunken aim could make the bullet go anywhere, with ricochets causing lots of physics based destruction and often causing you to accidentally (and hilariously) shoot yourself. Your wonky aim can make even simple shots hard to hit, and as you progress through the levels things get even harder, with you having to pull of trick shots to hit the targets.<br \/>\r\n<br \/>\r\nThe super hard difficulty could make Bang! Bang! a frustrating experience, but thankfully even missed shots are a joy to behold thanks to its fun sense of humour, quick restarts and chaotic physics based carnage caused by your shooting. Well worth checking out for some super silly drunken shooter action.","short_description":"BANG! BANG! Totally Accurate Redneck Simulator is a silly and super tough physics based shooter puzzler in which you attempt to help a drunken redneck hit targets without accidentally shooting himself with a ricochet.","supported_languages":"English","reviews":"\u201cBang! Bang! is simple, silly and very addictive\u201d<br><a href=\"https:\/\/steamcommunity.com\/linkfilter\/?url=http:\/\/www.alphabetagamer.com\/bang-bang-beta-demo\/\" target=\"_blank\" rel=\"noopener\" >http:\/\/www.alphabetagamer.com\/bang-bang-beta-demo\/<\/a><br><br>\u201cYeah, Bang Bang is that stupid. I hate it.\u201d<br><a href=\"https:\/\/youtu.be\/SmtCuejRt0k\" target=\"_blank\" rel=\"noreferrer\" >Blitz<\/a><br>","header_image":"https:\/\/steamcdn-a.akamaihd.net\/steam\/apps\/651380\/header.jpg?t=1525605971","website":"http:\/\/www.indiedb.com\/games\/bang-bang","pc_requirements":{"minimum":"<strong>Minimum:<\/strong><br><ul class=\"bb_ul\"><li><strong>OS:<\/strong> Windows XP Service Pack 3 or newer<br><\/li><li><strong>Processor:<\/strong> An Intel Pentium 4 processor or later that's SSE2 capable<br><\/li><li><strong>Memory:<\/strong> 512 MB RAM<br><\/li><li><strong>Graphics:<\/strong> Graphics card with latest drivers<br><\/li><li><strong>Storage:<\/strong> 500 MB available space<\/li><\/ul>","recommended":"<strong>Recommended:<\/strong><br><ul class=\"bb_ul\"><li><strong>OS:<\/strong> Windows 7 or newer<br><\/li><li><strong>Processor:<\/strong> 2 GHz dual-core processor or later that's SSE2 capable<br><\/li><li><strong>Memory:<\/strong> 2048 MB RAM<br><\/li><li><strong>Graphics:<\/strong> A nVidia or AMD graphics card with latest drivers, at least 512 MB of dedicated video memory<br><\/li><li><strong>Storage:<\/strong> 500 MB available space<\/li><\/ul>"},"mac_requirements":{"minimum":"<strong>Minimum:<\/strong><br><ul class=\"bb_ul\"><li><strong>OS:<\/strong> Mac OS X 10.6 or later<br><\/li><li><strong>Processor:<\/strong> An Intel Pentium 4 processor or later that's SSE2 capable<br><\/li><li><strong>Memory:<\/strong> 512 MB RAM<br><\/li><li><strong>Graphics:<\/strong> Graphics card with latest drivers<br><\/li><li><strong>Storage:<\/strong> 500 MB available space<\/li><\/ul>","recommended":"<strong>Recommended:<\/strong><br><ul class=\"bb_ul\"><li><strong>OS:<\/strong> Mac OS X 10.9 or later<br><\/li><li><strong>Processor:<\/strong> 2 GHz dual-core processor<br><\/li><li><strong>Memory:<\/strong> 2048 MB RAM<br><\/li><li><strong>Graphics:<\/strong> A nVidia or AMD graphics card with latest drivers, at least 512 MB of dedicated video memory<br><\/li><li><strong>Storage:<\/strong> 500 MB available space<\/li><\/ul>"},"linux_requirements":{"minimum":"<strong>Minimum:<\/strong><br><ul class=\"bb_ul\"><li><strong>OS:<\/strong> Ubuntu 10.04 + Debian 6 + OpenSuSE 11.3 + Fedora Linux 14<br><\/li><li><strong>Processor:<\/strong> An Intel Pentium 4 processor or later that's SSE2 capable<br><\/li><li><strong>Memory:<\/strong> 512 MB RAM<br><\/li><li><strong>Graphics:<\/strong> Graphics card with latest drivers<br><\/li><li><strong>Storage:<\/strong> 500 MB available space<\/li><\/ul>","recommended":"<strong>Recommended:<\/strong><br><ul class=\"bb_ul\"><li><strong>OS:<\/strong> 64-bit Ubuntu 14.04+, Debian 8+, openSUSE 13.3+, or Fedora Linux 24+<br><\/li><li><strong>Processor:<\/strong> 2 GHz dual-core processor<br><\/li><li><strong>Memory:<\/strong> 2048 MB RAM<br><\/li><li><strong>Graphics:<\/strong> A nVidia or AMD graphics card with latest drivers, at least 512 MB of dedicated video memory<br><\/li><li><strong>Storage:<\/strong> 500 MB available space<\/li><\/ul>"},"developers":["Dudarev Alexandr Vladimirovich"],"publishers":["Deklazon"],"price_overview":{"currency":"EUR","initial":199,"final":199,"discount_percent":0,"initial_formatted":"","final_formatted":"1,99\u20ac"},"packages":[183524],"package_groups":[{"name":"default","title":"Buy BANG! BANG! Totally Accurate Redneck Simulator","description":"","selection_text":"Select a purchase option","save_text":"","display_type":0,"is_recurring_subscription":"false","subs":[{"packageid":183524,"percent_savings_text":"","percent_savings":0,"option_text":"BANG! BANG! - 1,99\u20ac","option_description":"","can_get_free_license":"0","is_free_license":false,"price_in_cents_with_discount":199}]}],"platforms":{"windows":true,"mac":false,"linux":true},"categories":[{"id":2,"description":"Single-player"}],"genres":[{"id":"1","description":"Action"},{"id":"4","description":"Casual"},{"id":"23","description":"Indie"},{"id":"28","description":"Simulation"},{"id":"70","description":"Early Access"}],"screenshots":[{"id":0,"path_thumbnail":"https:\/\/steamcdn-a.akamaihd.net\/steam\/apps\/651380\/ss_f10575edcc1203c284c3228c11aa2279557d515b.600x338.jpg?t=1525605971","path_full":"https:\/\/steamcdn-a.akamaihd.net\/steam\/apps\/651380\/ss_f10575edcc1203c284c3228c11aa2279557d515b.1920x1080.jpg?t=1525605971"},{"id":1,"path_thumbnail":"https:\/\/steamcdn-a.akamaihd.net\/steam\/apps\/651380\/ss_217843100981af590bb4d6a340e5793a9b201cc4.600x338.jpg?t=1525605971","path_full":"https:\/\/steamcdn-a.akamaihd.net\/steam\/apps\/651380\/ss_217843100981af590bb4d6a340e5793a9b201cc4.1920x1080.jpg?t=1525605971"},{"id":2,"path_thumbnail":"https:\/\/steamcdn-a.akamaihd.net\/steam\/apps\/651380\/ss_927fb411856a759977c5c923079831f210d276e3.600x338.jpg?t=1525605971","path_full":"https:\/\/steamcdn-a.akamaihd.net\/steam\/apps\/651380\/ss_927fb411856a759977c5c923079831f210d276e3.1920x1080.jpg?t=1525605971"},{"id":3,"path_thumbnail":"https:\/\/steamcdn-a.akamaihd.net\/steam\/apps\/651380\/ss_4160159ae71c53355f6e4514af26bd27f0234522.600x338.jpg?t=1525605971","path_full":"https:\/\/steamcdn-a.akamaihd.net\/steam\/apps\/651380\/ss_4160159ae71c53355f6e4514af26bd27f0234522.1920x1080.jpg?t=1525605971"},{"id":4,"path_thumbnail":"https:\/\/steamcdn-a.akamaihd.net\/steam\/apps\/651380\/ss_e19d5f01f2925474e3c3a1d32eb5fbbdb4946b54.600x338.jpg?t=1525605971","path_full":"https:\/\/steamcdn-a.akamaihd.net\/steam\/apps\/651380\/ss_e19d5f01f2925474e3c3a1d32eb5fbbdb4946b54.1920x1080.jpg?t=1525605971"},{"id":5,"path_thumbnail":"https:\/\/steamcdn-a.akamaihd.net\/steam\/apps\/651380\/ss_ce22f426923604a38e4814f2681c444a54c14701.600x338.jpg?t=1525605971","path_full":"https:\/\/steamcdn-a.akamaihd.net\/steam\/apps\/651380\/ss_ce22f426923604a38e4814f2681c444a54c14701.1920x1080.jpg?t=1525605971"},{"id":6,"path_thumbnail":"https:\/\/steamcdn-a.akamaihd.net\/steam\/apps\/651380\/ss_ad9c8c69dc4e7b36de1100af0053d23162b8e499.600x338.jpg?t=1525605971","path_full":"https:\/\/steamcdn-a.akamaihd.net\/steam\/apps\/651380\/ss_ad9c8c69dc4e7b36de1100af0053d23162b8e499.1920x1080.jpg?t=1525605971"},{"id":7,"path_thumbnail":"https:\/\/steamcdn-a.akamaihd.net\/steam\/apps\/651380\/ss_6fce0da7203fb0289c4ee6b29fad427838fe853e.600x338.jpg?t=1525605971","path_full":"https:\/\/steamcdn-a.akamaihd.net\/steam\/apps\/651380\/ss_6fce0da7203fb0289c4ee6b29fad427838fe853e.1920x1080.jpg?t=1525605971"}],"movies":[{"id":256686850,"name":"BANG! 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{ "add-comparisons": "Aggiungi confronti", "current-comparisons": "Confronti attuali", "current-indicators": "Indicatori attuali", "favorites": "Preferiti", "add-indicator": "Aggiungi indicatore", "volatility-indicators": "Indicatori di volatilità", "overlap-studies": "Studi sovrapposti", "momentum-indicators": "Indicatori Momentum", "price-transformation": "Trasformazione del prezzo", "statistical-functions": "Funzioni statistiche", "pattern-recognition": "Riconoscimento dei pattern", "bill-williams": "Bill Williams", "time-interval": "Intervallo di tempo", "chart-type": "Tipologia di grafico", "indicators": "Indicatori", "comparisons": "Confronti", "drawing-tools": "Strumenti grafici", "chart-template": "Modello del grafico", "share-chart": "Condividi il grafico", "share": "Condividi", "link": "Link", "embed-code": "Codice inserito", "download-as": "Scarica come", "candles": "Candele", "ohlc": "OHLC", "line": "Linea", "dot": "Punto", "line-dot": "Punto linea", "spline": "Spline", "table": "Tabella", "crosshair": "Mirino", "vertical-line": "Linea verticale", "horizontal-line": "Linea orizzontale", "tick": "Tick", "1-tick": "1 tick", "1-minute": "1 minuto", "1-hour": "1 ora", "1-day": "1 giorno", "ticks": "Tick", "minutes": "Minuti", "hours": "Ore", "days": "Giorni", "cancel": "Annulla", "ok": "Ok", "delete": "Cancella", "remove": "Rimuovi", "rename": "Rinomina", "back": "Indietro", "save": "Salva", "yes": "Sì", "no": "No", "load-chart-template": "Carica modello del grafico", "save-changes": "Salva le modifiche", "save-as": "Salva come", "upload-template": "Carica modello", "you-haven't-saved-any-templates-yet": "Non hai ancora salvato alcun modello", "name": "Nome", "this-field-is-required": "Questo campo è obbligatorio", "use-the-save-as-button-to-save-the-chart-settings-type-time-period-indicators-and-comparisons": "Usa il pulsante \"Salva come...\" per salvare le impostazioni del grafico, tipologia, periodo di tempo, indicatori e confronti", "open": "Apri", "high": "High", "low": "Low", "close": "Chiudi", "1t": "1t", "1m": "1 min", "2m": "2 min", "3m": "3 min", "5m": "5 min", "10m": "10 min", "15m": "15 min", "30m": "30 min", "1h": "1h", "2h": "2h", "4h": "4h", "8h": "8h", "1d": "1g", "invalid-parameters": "Parametro(i) non valido(i)", "are-you-sure-you-want-to-delete-template?": "Sei sicuro di voler cancellare il modello?", "are-you-sure-you-want-to-overwrite-current-template?": "Sei sicuro di voler sostituire il modello attuale?", "template-changes-saved": "Modifiche apportate al modello salvato", "invalid-json-file": "File JSON non valido", "invalid-template-type": "Tipo di modello non valido", "successfully-applied-the-template-and-saved-it-as": "Il modello è stato correttamente applicato e salvato come", "downloading-template-as": "Download del modello come", "template-name-already-exists": "Il nome del modello esiste già", "addremove-indicators": "Aggiungi/Rimuovi indicatori", "addremove-comparisons": "Aggiungi/Rimuovi i confronti", "error-getting-data-for-1": "Errore durante il recupero dei dati per %1", "downloading-csv": "Download in corso di .csv", "stroke-width": "Larghezza del tratto", "stroke-color": "Colore del tratto", "you-do-not-have-any-active-indicators": "Non hai alcun indicatore attivo", "choose-from-any-indicator-in-our-list-to-get-started": "Per iniziare scegli un qualsiasi indicatore presente nel nostro elenco", "you-do-not-have-any-favorite-indicators": "Non hai alcun indicatore preferito", "active": "Attivo", "all": "Tutto", "popular": "Popolare", "view-popular-indicators": "Visualizza gli indicatori popolari", "view-all-indicators": "Visualizza tutti gli indicatori", "template-changes-saved-as": "Modifiche apportate al modello salvato come" }
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"\n少带旧家具,多带新思想\n道理虽浅,已经成章。墙上无名者的照片\n有如向日葵,每个人都还长着前世的面容\n一一活在贺城,狮城的农耕史上\n\n山还水,水还在,子孙们都在\n贺城,狮城,来过很多人,又渐渐走了\n有的像我远亲,有的是近邻,半个世纪了\n他们搬离阳光,去水底隐居\n他们的姓氏连同乳名,很快被遗忘\n\n城外的芹川,山路十八弯\n水流九曲连环,水还是白色\n山依然黛青,虽然黑白分明\n山和水却从不开口说话,谁都不讨好谁\n世界没有中心,一条河流走着走着\n就迷失了方向,水底的村庄平静而安逸\n\n离家千里,记忆与梦境很容易混在一起\n顾名思义的那种孤独,相忘于江湖\n一个人在小路上漫步,月亮是旧的\n风中时常遇见古人,他们落英果腹,沧桑为饮\n\n从一个地方到另一个地方,无需字斟句酌\n人生改变其实很简单,有如某年某月某日\n某人到此一游,本意是英雄救美,在水一方\n湖边做巢,风花雪月。世间的每一寸净土\n都是有花有水的地方,只要让心拐个弯\n村庄虚影的背后,一条河流,加上另一条河流\n就到达上帝居住的天堂\n\n身在水兮心在岸,虚幻的永恒\n我们总是一厢情愿,想把镜花水月合二为一\n太阳首先失去耐心,躲到山的背面\n天开始黑下来,天空变得模糊\n夜色很快沉默地努力向远处无限延伸\n却始终无法与山顶的灵魂会合"
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