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5455987#0
月球到地球的距离是多少?
[ { "docid": "1630640#0", "text": "月球距離 (LD) 是天文學上從地球到月球的距離,從地球到月球的平均距離是384,401公里 (238,856英里)。因為月球在橢圓軌道上運動,實際的距離隨時都在變化著。", "title": "月球距離" }, { "docid": "155695#21", "text": "這是儒勒·凡爾納在從地球到月球這本書中所提到的方法: 直到此刻,許多人仍然不知道如何計算地球與月球相隔的距離。他們的環境教導他們這個距離是通過視差的觀察和測量得到的。如果視差這個字令他們感到迷惑,他們被告知這是從地球半徑的兩端連接到月球的兩條直線的對角。如果他們懷疑這種方法的完備性,他們立刻可以看到的不只是地球到月球平均距離的數值,234,347英里(94,330leagues),並且誤差小於70英里(大約30leagues)。", "title": "视差" }, { "docid": "1694875#2", "text": "2006年7月3日,在北美洲西海岸上空近距离掠过地球。最近距离为432308千米,即0.00289天文单位,仅是月球到地球平均距离的1.1倍。在它接近地球时,位于美国莫哈维沙漠的戈尔德斯通、西西里岛以及乌克兰叶夫帕托里亚RT-70射电望远镜等三处射电望远镜、其他地方的光学望远镜和天文爱好者对它进行密切观测。", "title": "2004 XP14" } ]
[ { "docid": "97610#4", "text": "阿里斯塔克斯认为太阳,月球和地球在每个月的首个或最后的四分之一时期内,构成了一个近似的直角三角形。他估计最大角约为87°。尽管他应用的几何理论没有错,但由于观测数据有偏差,他得出了日地距离是月地距离的20倍的结论。事实上,前者是后者的390倍。阿里斯塔克斯指出,月球和太阳有几乎相同的视角,因此他们的直径与他们到地球的距离是成正比的。尽管計算結果是錯誤的,他的方法卻符合逻辑。这指出了太阳明显大于地球,恰恰可以用来证明日心说模型。", "title": "阿里斯塔克斯" }, { "docid": "155695#23", "text": "測量地球到月球距離最原始的方法是在阿里斯塔克斯的《太陽和月球的距離與大小》一書中提出。他注意到太陽、月球和地球在上弦和下弦會形成直角三角形(月球位於直角上)。然後,他估計出月球、地球和太陽的夾角是87°。使用正確的幾何學,但不正確的觀測資料,阿里斯塔克斯推論太陽的距離略低於月球距離的20倍。但是,這個角度的正確數值接近89° 50',而太陽的實際距離比月球遠了約390倍。他指出月球和太陽有著幾乎一樣的視角大小,因此它們的直徑和與地球的距離有著相同的比值。因此,他也估計太陽比月球大20倍左右;這一結論,儘管源於不正確的資料,但他的邏輯是正確的。他也明確的表示太陽大於地球,這可以支持日心說的模型。", "title": "视差" }, { "docid": "5414300#75", "text": "太陽的直徑大約是月球的400倍,但它與地球的距離也是400倍遠,因此地球看到的月球和太阳大小几乎相同。这一原因正好使得兩天體的角直徑(或是立體角)吻合,因此地球能观测到日全食和日環食。", "title": "地球" }, { "docid": "1710085#12", "text": "在角距離最大時,很容易分辨出地球和月球是一對雙星,但是大約一星期之後它們會合併成一個光點 (以裸眼觀看),而大約再過一個星期,月球又會在相對的另一側分離到最大的角距離。月球和地球分離的最大角度也和地球和火星的距離相關:在地球最接近火星時 (接近內合) 大約有17',而當距離最遠時 (接近外合) 就只有3.5'。做為比較,從地球看月球的視直徑是31'。", "title": "火星天文學" }, { "docid": "10037#11", "text": "在西元2世紀,托勒密估計太陽的平均距離是地球半徑的1210倍。要確定這個值,托勒密測量了月球的視差,發現月球的的平視差是1° 26′,而這個值比實際的大了許多。然後他推導出月球的最大距離是地球半徑的64 1/6倍。由於他的視差圖和它的月球軌道理論中的錯誤互相抵消,因此這一數值大致上是接近正確值的。然後,他測量太陽和月球的視大小,並得出結論認為太陽表面的直徑和月球在最大距離時的月球直徑一樣,並且從月食的紀錄,他以月食時月球通過地球影錐的時間估計影錐的視直徑。從這些數據,地球到太陽的距離可以利用三角學算出是地球半徑的1210倍。這使太陽和月球距離的比率大約是19倍,符合阿里斯塔克斯匹配的圖形。雖然從理論上來說,托勒密的過程是可行的,但它對數據上微小的變化非常敏感,因此只要在測量上變更幾個百分點,就可以使太陽的距離變成無限大。", "title": "天文單位" }, { "docid": "5549079#23", "text": "地球上的大部分地方每天都会有两次满潮,间隔大约为12小时25分钟。此时间恰好是地球自转一周,加上月球运行到相对观测者同一位置时所需时间之和的一半。月球质量是太阳的2700万分之一,而地月距离是日地距离的400分之一。因为潮汐力随着距离的增加衰减得较快,所以月球对地球的潮汐影响大约是太阳的两倍多。地球上距离月球最近处的洋面由于受到较强的引力会出现隆起;地球背面受到的月球引力最弱,也会形成一个相似的隆起。这些隆起会像月球一样绕着地球旋转。太阳的引力影响则相对小得多,但在满月或新月时,日月地处于同一直线产生的引力效应导致了大潮(spring tide)的出现。反之,当太阳与月球成90°角时,相对的引力效应就会减小,形成小潮(neap tide)。", "title": "海" }, { "docid": "747998#0", "text": "月球軌道是指月球圍繞地球的軌跡。月球以27.323天完整的環繞地球一圈。地球和月球的質心在距離地心4,700公里處(地球赤道半徑的⅔),兩者各自圍繞著質心運轉。月球與地球中心的平均距離是385,000公里,大約是地球半徑的60倍。軌道的平均速度是1.023公里/秒,月球在恆星的背景之間大約每小時移動0.5°,這相當於月球的視直徑。月球的軌道不同於大部分行星的天然衛星,它是接近黃道平面,而非地球的赤道平面。月球軌道面相對於黃道平面的傾斜只有5.1°,自轉軸的傾角也只有1.5°。", "title": "月球軌道" } ]
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1901870#0
郑州市位于中国哪个省?
[ { "docid": "7423748#0", "text": "郑州市民公共文化服务区是位于中国河南省郑州市中原区的文化中心,又称郑州中央文化区或郑州CCD()。区域范围为南水北调总干渠以南,陇海路以北,凯旋路以西,西四环以东,总占地1.53平方公里,总投资300亿。区域内主要建设“四个中心”,即奥体中心、市民活动中心、文博艺术中心和现代传媒中心。这些建筑群于2015年12月1日开工。", "title": "郑州市民公共文化服务区" }, { "docid": "86594#0", "text": "郑州商城遗址位于中国河南省郑州市,是商代都城的遗址,年代距今3500年左右。1950年发现,1955年发现了内城的城墙,1961年国务院列为中国全国重点文物保护单位。", "title": "郑州商城遗址" }, { "docid": "8352#0", "text": "郑州市,简称“郑”,古称商都,今为绿城,是河南省的省会,国家历史文化名城,国家中心城市,中国特大城市,重要的综合交通枢纽。郑州市是全省重要的铁路、航空、高速公路、电力、邮政电信主枢纽城市,拥有全國首个国家级航空港经济综合实验区-郑州航空港经济综合试验区。郑州市是中国普通铁路和高速铁路网中唯一的“双十字”中心,也是首批跨境电子贸易试点城市和国家级互联网骨干直联点城市。", "title": "郑州市" }, { "docid": "8352#52", "text": "郑州市是国家公路网主要枢纽之一,以郑州为中心的中原城市群地区是中国高速公路网密度较大的区域之一。和两条国家高速公路在郑州交汇,、、、和亦从郑州穿境而过。除此之外,以郑州市为起点,还有、、、、等省级高速公路,以及通往开封、新乡等周边城市的快速通道。这些公路连接郑州和省内外重要城市,从郑州出发,通过高速公路,3小时内可以到达河南省内任何一个省辖市。截至2017年底,郑州市公路通车里程达11,692.3公里,其中高速公路616.9公里,一级公路433.5公里,二级公路1,803.7公里,三级公路1,186.5公里,路网密度达每百平方公里157公里。", "title": "郑州市" }, { "docid": "8352#1", "text": "郑州位于河南省中部偏北,黄河下游。现辖6个市辖区(中原区、二七区、金水区、惠济区、管城区、上街区),代管5个县级市(荥阳市、登封市、巩义市、新郑市、新密市)和1个县(中牟县),全市总面积7,567.18平方公里,其中市区面积1,078.07平方公里。2018年,全市常住人口1012万,其中市区常住人口近600万。居民以汉族为主,母语为中原官话的郑州方言。", "title": "郑州市" }, { "docid": "296460#0", "text": "郑州站位于河南省郑州市二七区,是中国铁路郑州局集团辖下的特等站,为中国铁路最重要的枢纽之一。京广铁路及陇海铁路两大铁路干线在此交汇。此外,郑州站亦为郑焦城际铁路的始发终到站,郑西高速铁路亦通过郑荥联络线接入本站。", "title": "郑州站" }, { "docid": "3144625#0", "text": "郑州博物馆成立于1957年7月1日,原名郑州市文物陈列室。1965年更名为郑州博物馆,是一座地方性博物馆。馆名由郭沫若题写。原址位于中国河南省郑州市建设东路碧沙岗公园北伐军阵亡将士烈士祠,建于1928年8月。1999年12月28日,位于嵩山南路168号的嵩山路馆建成开放,并更名为郑州博物馆。2008年,郑州博物馆获评首批“国家一级博物馆”。", "title": "郑州博物馆" }, { "docid": "7422729#0", "text": "郑州美术馆是位于中国河南省郑州市中原区的综合性美术馆,隶属于郑州市文化广电和旅游局。1995年4月20日,郑州美术馆瑞达馆开工建设,位于郑州高新技术产业开发区瑞达路83号,1997年10月30日建成并对外开放。瑞达馆占地面积28.4亩,建筑面积5,200平方米,展厅面积1,800平方米。", "title": "郑州美术馆" }, { "docid": "598969#0", "text": "郑州东站位于中国河南省郑州市郑东新区,东邻东三环路,西北距郑州国际会展中心约3公里,于2012年9月28日启用。郑州东站为京广高速铁路和徐兰客运专线的枢纽中间站,同时亦是郑渝高速铁路、郑阜高速铁路、郑开城际铁路和郑机城际铁路的始发站,原为中国铁路郑州局集团的直属特等站,2020年4月7日整体建制合并至郑州车站。郑州东站规模16台32线,总建筑面积41.2万平方米,为郑州市规划的四座主要客运站之一,亦是华中地区重要的铁路客运枢纽。", "title": "郑州东站" } ]
[ { "docid": "8352#25", "text": "郑州位于东经112°42'-114°14' ,北纬34°16'-34°58',东西宽166公里,南北长75公里,总面积约为7446.2平方公里,其中市区面积约1010.3平方公里,山地面积约2377平方公里,全市水面面积约11.4平方公里。但随着南水北调中线工程的实施,以及郑州市生态水系工程的开展,郑州市的水域面积将会不断增加。郑州北临黄河,西依嵩山,东南为广阔的黄淮平原,东面是开封市,西面为古都洛阳市,南面是许昌市,北面为焦作市和新乡市。", "title": "郑州市" } ]
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5061019#0
彩虹有几种颜色?
[ { "docid": "6245064#0", "text": "彩虹,又稱天弓、天虹、絳等,簡稱虹,是氣象中的一種光學現象,當太陽光照射到半空中的水滴,光線被折射及反射,在天空上形成拱形的七彩光譜,由外圈至内圈呈紅、橙、黃、綠、蓝、靛蓝、藍紫七种颜色(霓虹則相反)。事實上彩虹有无数種顏色,比如,在紅色和橙色之間還有許多種細微差別的顏色,根據不同的文化背景被解讀爲3-9種不等,通常只用六七種顏色作為區別。國際LGBT聯盟的彩虹旗为六色:紅橙黃綠藍紫。紅橙黃綠藍靛紫的七色說,就是在六色基礎上將紫色分出偏藍色的靛。傳統中國文化說的七色是:赤橙黃綠青藍紫,青色就是偏藍的綠色。要是把橙色也分爲偏紅、偏黃的兩種就是九色。三色說有:紅綠藍,就是光學三原色,所有顏色的光都是這三種顏色混合出來的,和亚里士多德紅、綠、紫三色說,就是兩頭加中間。", "title": "彩虹" }, { "docid": "37842#3", "text": "一个虹所表现的每个颜色只包含一个波长的光。我们称这样的颜色为单色的。虹的光谱实际上是连续的,但一般來說,人们将它分为七种颜色:红、橙、黄、绿、青、蓝、紫(或者红、橙、黄、绿、蓝、靛、紫);每个人的分法总是稍稍不同。单色光的强度也会影响人对一个波长的光所感受的颜色,比如暗的橙黄被感受为褐色,而暗的黄绿被感受为橄榄绿,等等。", "title": "颜色" }, { "docid": "6245064#16", "text": "“霓”是与“虹”相对应的一种自然现象。虹是下雨天以及在雨后天晴之际,阳光穿透还残余在空气中的水珠而发生折射,散射出七彩的光芒。彩虹形状多为弧形,出现在和太阳相对着的方向,从外(半径大的)弧至内弧的颜色依次为红、橙、黄、绿、蓝、靛、紫。霓也叫“副虹”,形成与彩虹原理大致相同,只是光线在水珠中的反射多了一次,彩带排列的顺序和彩虹相反,红在内,紫在外。而彩虹和霓主要也是因為折射和反射的次數上之差別,導致色彩的排列剛好相反。", "title": "彩虹" } ]
[ { "docid": "6245064#35", "text": "后来古人注意到,彩虹有时成双成对地出现,一个在上,一个在下,而且两者颜色的顺序相反:一个红色在外、紫色在内、色彩鲜艳,另一个红色在内、紫色在外、颜色暗淡一些。于是古人继续展开他们神奇的想象力: 根据阴阳学说,颜色顺序相反意味着阴阳属性相反,一个为阳另一个为阴,并且彩虹是一种动物,那就是一个是雄一个是雌。就这样,他们得出了惊人的结论:彩虹分男女!", "title": "彩虹" }, { "docid": "235011#7", "text": "“彩虹效应”是单片DLP投影仪所特有的现象。如前所述,因为单片DLP投影仪使用一个色轮来控制颜色,那么在任一特定时刻,屏幕上出现的其实只有一种颜色。如果人的目光在投影屏幕前快速晃动,那么合成画面的组合颜色(任一个特定时刻的红绿蓝三种颜色的画面)将会是对肉眼可见的。单片DLP投影仪的生产商使用更快的色轮转速,以及更多的色轮颜色段数来消除这一先天缺陷,这就是我们现在在市场上所看到的2倍速、3倍速或者4倍速色轮了。例如,一个六段色轮(红绿蓝红绿蓝)以2倍速的转速转动,那么其带来的结果将是4倍速色轮。另外一种方法是将分段色轮变为阿基米德螺旋色轮,这样的色轮是使颜色在屏幕的上下移动。普通的分段式色轮在颜色与颜色的转换之间会有一个短暂的暂停,这就意味着如果色轮的颜色段数越多投影图像就会越暗一些(反之段数越少图像越明亮)。使用了螺旋色轮,微镜器件就会在同一时刻在屏幕上投射出不止一种颜色,每一种颜色都随着色轮的转动而上下移动。", "title": "数字光处理" }, { "docid": "348056#7", "text": "虹膜有多种颜色,这并不影响视力。虹膜通常帶有色素,人類虹膜中最常見的是褐色 (含黑褐色和棕色)與藍色,另外還有綠色、灰色和琥珀色。白化症患者則有粉紅色、紫色的虹膜,這是由於其虹膜中沒有色素,只能顯示出微血管的顏色。", "title": "虹膜" }, { "docid": "472273#5", "text": "过去通常认为人類虹膜的基色只有三種:褐色、藍色和綠色,其他顏色的虹膜則是這三種顏色的變體。但这一分类方法被批评为过于简化。近来研究把虹膜颜色分为九种。人类虹膜颜色在儿童期会发生戏剧性改变。另外,有的人具有蓝色或绿色虹膜但围绕瞳孔为褐色环,这使得眼睛色彩的分类更为复杂。", "title": "眼睛色彩" }, { "docid": "403660#43", "text": "杭州地铁的每条地铁线路分别用不同种色彩表示,主要由彩虹色作为配色方案。该配色方案由中国美术学院设计,初期储备有21种颜色,其中以赤橙黄绿青蓝紫7种自然色作为第一色系,另有两套在第一色系的基础上在明暗度做出调整的色系。每种颜色均以植物名称命名。", "title": "杭州地铁" }, { "docid": "1547261#1", "text": "彩虹桥位于顺德区大良街道凤山桥(凤山西路)之上,横跨大良河。桥内部空心,由钢索组成,外面包裹喷有七种颜色涂料的铁皮。彩虹桥的造型是两条垂直交叉的彩虹,从高处俯视看是一个叉形,有人认为它像虾筝(一种当地人在河里捕鱼虾的工具),当地老一辈的人对“虾筝”很反感,因为他们认为当一个人没钱、倒霉、走投无路的时候才会去河边用到这个工具抓鱼虾维持生计。", "title": "彩虹桥 (顺德)" }, { "docid": "1893802#0", "text": "彩虹色或虹彩(),是一种结构色。彩虹色常见于肥皂泡、蝴蝶翅膀、贝壳等物体。 如果观测物体表面的角度改变,色彩也随之改变,这样一种光学现象就叫做虹彩现象,即彩虹色。", "title": "彩虹色" } ]
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1176286#0
唐朝的开国皇帝是谁?
[ { "docid": "686#0", "text": "唐朝(中古漢語:dang - IPA,),中國歷史上的朝代,國祚共历289年,23位皇帝。由唐高祖李淵所建立。李渊祖父李虎在南北朝的西魏是八柱国之一,封为隴西郡公。其孫子李淵在北周及隋朝受封唐國公。隋朝末年天下大亂,時為晋阳(今山西省太原市)留守的李渊于617年在晋阳起兵,同年攻入長安(今陕西省西安市),618年接受隋恭帝楊侑禪位,建立唐朝,是為高祖,定都長安;690年到705年为武周,定都洛阳。", "title": "唐朝" }, { "docid": "5402099#15", "text": "这一成果使李渊成为帝位的一位主要竞争者,但当时尽管将军们呼吁他在那里称帝,他仍然伪装成隋朝忠臣:他保证隋朝皇室的安全且尊重他们,年轻的杨侑被立为隋恭帝,炀帝被尊为太上皇。直到距离杀死副手、正式与隋决裂后一年的618年6月16日,李渊才废黜傀儡皇帝,自称为唐朝开国皇帝,庙号高祖。新皇朝仍然要面对全国各地涌现的叛军和军阀,但在贞观二年(628年),恩威并施的唐朝成功将中国安抚和统一在自己的统治下。", "title": "霍邑之战" }, { "docid": "686#11", "text": "唐朝皇室先祖為南北朝時期的李虎,他因功被封為西魏北周的八柱國之一。隋朝建立後,隋文帝封李虎之子李昞為唐國公,後由李昞之子李淵繼承爵位。李渊受隋炀帝重用,於616年被派為太原留守,但隋炀帝對他也不放心,派王威與高君雅監督之。隋朝在大業年间,由於隋炀帝過度使用國力與三征高句丽的失败,使得各地民變不止,史稱隋末民变。李渊見天下大亂,隋朝的灭亡不可扭转,便生起取而代之的念头。617年李淵殺王威、高君雅,在太原起兵造反。不久,李淵率諸子眾將攻破守備關中的屈突通,占領隋都大興城。李淵擁立楊侑為帝,是為隋恭帝,遙尊隋煬帝為太上皇,自任大丞相,進封唐王。而在揚州的隋煬帝,他心灰意冷,不願返回關中,最後於618年的江都政變中被宇文化及等叛軍殺害。李淵藉此機會,於同年五月迫使隋恭帝禅位,建國唐朝,即唐高祖。都城大兴改名為长安,封嫡長子李建成為太子、嫡次子李世民為秦王、嫡四子李元吉為齊王。", "title": "唐朝" } ]
[ { "docid": "3503834#0", "text": "开国皇帝是中国两千多年封建帝制社会中的各个朝代的创立者,但未称帝有奠基作用的不算在内。开国皇帝是封建专制统治的象征与代表。自公元前221年秦始皇嬴政統一六國後自称皇帝始,中国历史上包括割据政权和少数民族政权在内的开国皇帝约有100人。", "title": "中国开国皇帝列表" }, { "docid": "1506772#1", "text": "主要包括秦王李世民率军平定薛举·薛仁果(薛仁杲)父子(618年)、刘武周·宋金刚(619年-620年)、王世充(620年-621年)、窦建德(621年)、刘黑闼(621年-622年)的战争,与赵郡王李孝恭、李靖平定萧铣(621年)、辅公祏(623年-624年)的战争,吴王杜伏威平定李子通(620年-621年)、林士弘(621年-622年)的战争,太子李建成平定刘黑闼(622年-623年)的战争。", "title": "唐朝开国战争" }, { "docid": "4548049#5", "text": "天祐四年(907年),朱全忠迫唐哀帝禅位于他,灭唐建立后梁,为太祖皇帝。包括杨渥、李茂贞、河东节度使李克用、西川节度使王建在内的几位节度使拒绝承认梁帝。王建自建前蜀政权,杨渥和二李理论上仍为已灭亡的唐朝的封臣,实际为各自分离的政权弘农、岐、晋的领主。", "title": "李俨 (唐朝至五代)" }, { "docid": "7615#0", "text": "唐玄宗李隆基(公元),685年出生在洛阳,唐朝第九代皇帝(712年-756年在位);在位44年,享寿77岁,是唐朝在位最久与最长寿的皇帝,唐睿宗第三子,母窦德妃。庙号玄宗,谥号至道大圣大明孝皇帝。宋代避聖祖趙玄朗讳,清代避諱康熙帝「玄燁」,皆称为唐明皇,另有尊号“开元圣文神武皇帝”。年輕時性格英明果断,勇敢有為,善於謀略,多才多艺,知人善任,頗有曾祖父唐太宗之風範。知晓音律,至今留下許多樂曲,擅长书法,儀表雄伟俊丽。", "title": "唐玄宗" }, { "docid": "18658#5", "text": "宋朝的開國皇帝是趙匡胤,庙号太祖。他本來是后周的殿前都點檢,掌管禁軍,乃職業軍人。趙匡胤由於戰功卓著,成為了後周世宗的左膀右臂。世宗死後,繼位的恭帝年幼,后通過陈橋兵變奪取後周政權,建立北宋王朝。", "title": "北宋" }, { "docid": "455116#9", "text": "第一位为后突厥汗国登利可汗(734年—741年在位),不过登利既无默啜可汗的勇武,也无毗伽可汗的大智,可以说后突厥实亡于登利;从石国吐屯王·伊捺吐屯屈勒向唐玄宗于公元741年上表的《请讨大食表》文中“后背天可汗,脚底火起。今突厥属天可汗”,可见唐朝皇帝在突厥人心目中仍是天可汗,尤其在西突厥诸族中。另外,后突厥毗伽可汗于公元716年“欲南下为寇”,其身边的著名宰相暾欲谷也曾劝说曰:「唐主(唐玄宗)英武,民和年丰,未有间隙,不可动也。我众新集,力尚疲羸,且当息养数年,始可观变而举」。其后,安史之乱爆发,唐朝皇帝威严受损,而回纥由于助唐有功,也开始以天可汗汗号自許,包括药罗葛氏牟羽可汗(759年—780年在位)、阿跌氏懷信可汗(795年—805年在位)之后的回纥可汗。", "title": "天可汗" }, { "docid": "23557#0", "text": "唐中宗李顯(),后改名李哲,是唐朝的第四和第六任皇帝,两次在位:第一次在位时间为684年1月3日-684年2月26日,第二次在位时间为705年2月23日-710年7月3日。唐中宗前后两次当政,共在位五年半,公元710年病逝,终年55岁,谥号大和大圣大昭孝皇帝(初谥孝和皇帝),葬于定陵。", "title": "唐中宗" } ]
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1855#0
法国总统是谁?
[ { "docid": "5682333#2", "text": "2017年5月15日,法国总统艾曼紐·马克龙任命其为法国总理。", "title": "爱德华·菲利普" }, { "docid": "7373002#0", "text": "2022年法国总统选举第一轮投票将于2022年4月8日至23日举行,第二轮将在第一轮的两周后举行。若没有候选人在第一轮投票中获得多数票,两周后将在前两名候选人之间进行决赛。法国现任总统为埃马纽埃尔·马克龙,他赢得2017年大选,任期至2022年5月13日。", "title": "2022年法国总统选举" }, { "docid": "543#44", "text": "总统是法国的国家元首,拥有任免总理,主持内阁会议和颁布法律的权力,同时也是国家军队的最高司令,由普选直接产生,经过两轮投票,获过半数支持的候选人当选总统。总统任期原本为七年,2000年9月24日法国全民公投之后确立总统任期由七年缩短为五年,并最多可连任二次。总统主持内阁会议,颁布法律;总统亦是三军统帅。另外,根据宪法第16条,在面临重大危机时,总统拥有采取非常措施的权力,例如宣布国家进入紧急状态或启动全国动员令等,并有权解散国民议会。目前的总统为埃马纽埃尔·马克龙,是法兰西共和国的第二十五任总统,于2017年5月14日正式上任。", "title": "法国" }, { "docid": "7144686#0", "text": "弗洛朗斯·帕尔丽(Florence Parly,)是一位法国政治人物,自2017年起担任总统埃马纽埃尔·马克龙政府的。她曾是社会党成员,曾在2000年至2002年担任雅克·希拉克总统的。", "title": "弗洛朗斯·帕尔丽" } ]
[ { "docid": "1595055#1", "text": "法国总统是法兰西共和国的国家元首。現時的法國是第五共和,根据1958年的《法国宪法》,法国总统执掌行政权,由人民直接选举产生,任期5年(2002年前任期为7年),可连选连任一次。总统是国家元首和武装部队司令。法国自1958年起实行半总统半议会民主制;因此根据新宪法,总统具有很大权力,有权力解散国民议会,组织全民大选,以及在国家非常时期采取必要措施的全权等;同时总统有权任命总理和批准由总理提名的法国政府内阁成员。根据安道尔宪法,法国总统也是安道尔国家元首两大公之一。", "title": "法國政治" }, { "docid": "20461#0", "text": "这是一个法国总统的列表。首位法国总统通常被认为是在1848年大选中获胜的路易-拿破仑·波拿巴(后称帝成为拿破仑三世),当时法国处于第二共和时期。根据1958年的《法国宪法》,法国总统与总理领导的内阁执掌行政权,由全体法国合资格选民直接选举产生,任期5年(2002年前任期为7年),可连选连任一次。", "title": "法国总统列表" }, { "docid": "78627#0", "text": "法蘭西共和國總統(),簡稱法國總統,是法国的國家元首。總统是國家元首和武裝部隊最高司令。現今法國是法蘭西第五共和國,根據1958年法國憲法,法國總统與總理領導的內閣執掌行政權,由全體法國合資格選民直接選舉產生,任期5年(2002年以前任期為7年),可連選連任一次。另根据安道尔憲法,法國總统也是安道尔兩位國家元首之一(另一位是天主教烏赫爾教區主教)。", "title": "法国总统" }, { "docid": "493286#2", "text": "1958年的第五共和国宪法规定,总统是国家的最高职位,是国家行政权的执掌人,是军队的最高统帅,法兰西的最高法官,法兰西荣誉勋团的最高首长,也是安道尔公国的国家元首:两大公之一(但法国总统本身并不予以承认)。总统的职责包含了监督宪法的履行,政体的延续以及公共权力的正常运作。", "title": "2007年法国总统选举" }, { "docid": "46587#31", "text": "推翻帝制后的法国的国家元首主要是法国总统,此外还有维希政府的国家元首(1940年—1944年)、法兰西共和国临时政府的主席(1944年—1946年)和法兰西第五共和国期间的法国参议院议长(1969年和1974年)等不同称号的法国国家元首。不同的妄求者(觊觎王位者和觊觎帝位者)都自称是法国的正统君主,拒绝承认法国总统和其他法国国家元首。他们是历史上的法国君主的后裔,分属不同的集团,这些集团是:", "title": "法国君主列表" }, { "docid": "1923800#0", "text": "法国总理(法語:Premier ministre français),為法兰西第五共和国政府首脑(国家元首是法国总统)。在不同的历史时期,法国政府首脑的称呼也各不相同。在法兰西第三、第四共和国时期,政府首脑称作部长会议主席(Président du Conseil des Ministres,简称会议主席,Président du Conseil)。", "title": "法国总理列表" } ]
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4511218#0
孙子兵法是谁的著作?
[ { "docid": "355856#3", "text": "孙子的著作《孙子兵法》深受吳國歡迎,並在古今中外影响深远。", "title": "兵家" }, { "docid": "1120#0", "text": "《孫子兵法》,即《孫子》,又稱作《武經》、《兵經》、《孫武兵法》、《吳孫子兵法》,是中國古代的兵書,作者為春秋末期的齊國人孫武(字長卿)。一般認為,《孫子兵法》成書於專諸刺吳王僚之後至闔閭三年孫武見吳王之間,也即前515至前512年,全書為十三篇,是孫武初次見面贈送給吳王的見面禮;事見司馬遷《史記》:「孫子武者,齊人也,以兵法見吳王闔閭。闔閭曰:子之十三篇吾盡觀之矣」。", "title": "孙子兵法" }, { "docid": "1120#10", "text": "《漢書.藝文志》記載:「兵權謀家吳孫子兵法八十二篇,圖九卷」。八十二篇中的十三篇著於見吳王前;見吳王後又著問答多篇。晚至唐代,流傳的孫子兵法共三卷,其中十三篇為上卷,還有中下二卷。《孫子兵法》註家杜牧認為,曹操將八十二篇孫子兵法刪節為十三篇;但其他註家認為十三篇出自孫武本人,不是曹操刪節的結果。", "title": "孙子兵法" }, { "docid": "22171#24", "text": "吴国的军事家孙武及其著作《孙子兵法》,对中国的影响持续了几千年,直到今天。", "title": "吴国" } ]
[ { "docid": "1120#1", "text": "《孫子兵法》是世界上最早的兵書之一。被奉為中國兵家經典,後世的兵書大多受到它的影響,對中國的軍事學發展影響非常深遠。它也被翻譯成多種語言,在世界軍事史上具有重要的地位的著作。", "title": "孙子兵法" }, { "docid": "1137#11", "text": "《孙膑兵法》又称《齐孙子》,《汉书·艺文志》兵家权谋论著中记载孙膑著有《齐孙子》八十九篇、图四卷。《孙膑兵法》自《隋书·经籍志》便不见于历代正史文献著录,失传近1700年,造成历史上诸多对孙武、孙膑其人及其著作的质疑。1972年,在山东省临沂市银雀山汉墓同时出土了竹简本的《孙子兵法》和《孙膑兵法》,改变了学术界的认识。现存的《孙膑兵法》由出土的竹简整理而成,分上下两编共三十一篇。学术界认为上编是在孙膑著作和言论的基础上由其弟子辑录、整理而成;下编在内容上虽与上编类似,但在编撰体例上存在不同,是否为孙膑及其弟子所著尚无充分的证据。以下为《孙膑兵法》的篇目及主要内容:", "title": "孙膑" }, { "docid": "5934731#1", "text": "专辑基于公元前六世纪孙武的军事专著《孙子兵法》创作。《孙子》凡十三篇,每篇从不同角度切入来分析战争。据考证,该书所载即是当时的军事谋略。而此同名专辑收录了十三首歌曲,每首歌曲各自对应原著篇章。歌词则是根据一些应用了孙子战争思想的著名战役而创作,比如一战、二战。", "title": "孙子兵法 (专辑)" }, { "docid": "1136#1", "text": "《孙膑兵法》最早见于《汉书·艺文志》,东汉以后就已經失传。因此著名历史学家钱穆曾推测孙膑就是孙武,认为《孙膑兵法》就是《孙子兵法》。1972年,在山东临沂银雀山汉墓同时出土竹简本的《孙子兵法》和《孙膑兵法》,才改变了学界的认识。竹简本是汉初抄本,其中孙膑不以第一人称出现,所以学界普遍认为此书是由孙膑弟子纪录而成。现在分上下两编,共三十篇。", "title": "孙膑兵法" }, { "docid": "1751526#2", "text": "二十世纪七十年代,服部千春著述《新编孙子十三篇》(全五卷),1974年在他访华期间,将此书呈献给毛泽东,并说:“登山之路不一,望巅之月相同”。此书后来被中国兵法研究学者谢国良、吴如嵩的帮助下改作《孙子兵法校解》,1987年3月由中国军事科学出版社出版。毛泽东的“军事教育顾问”郭化若将军还为此书题写了书名。1975年,他又与中国著名书法家李铎合作出版了《孙子兵法新校字帖》,开创了《孙子》书法字帖的先河。", "title": "服部千春" }, { "docid": "1120#14", "text": "此書對中國古代的軍事學產生了巨大的影響,被奉為兵家經典。它是中國古代軍人必須研讀的一本軍事著作,許多著名的軍事家都對此書作過注解。", "title": "孙子兵法" } ]
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3429226#0
松鼠喜欢吃什么?
[ { "docid": "6973704#3", "text": "狐松鼠喜欢生活在开阔的橡树、松树林地,有非常灵敏的嗅觉、听觉和视觉,它们通过气味来交流。 不同地区的狐松鼠有不同的食物偏好。一般来说,其食谱包括紅橡、白蠟、七葉樹、山核桃、昆虫、鸟蛋和真菌,但也会吃玉米、大豆、燕麦、小麦等农作物。", "title": "狐松鼠" }, { "docid": "528100#3", "text": "一般认为,松鼠猴既以水果为食,也以昆虫为食,偏爱树上的莓类水果。被捕获后,松鼠猴常被喂以苹果、橘子、葡萄、香蕉之类的水果。它们也食用多种蔬菜,比如莴苣、芹菜和洋葱。松鼠猴也会捕食昆虫和小型脊椎动物如树蛙。松鼠猴主要从食物中摄取水分,也会从树洞和地上的水坑饮水。找不到水果的时候,松鼠猴也会食用花蜜。", "title": "松鼠猴" }, { "docid": "80820#4", "text": "松鼠一般以植食性為主,食物主要是種子和果仁,也會吃鸟蛋,水果如櫻桃、草莓等。部分物種會食昆蟲,其中一些熱帶物種更會為捕食昆蟲而進行遷徙,甚至叼走山雀雛鳥。", "title": "松鼠" } ]
[ { "docid": "528100#2", "text": "松鼠猴通常喜欢栖息在林冠的中部,有时候也会到地面活动,或者爬上林冠高处。它们喜欢雨林、热带草原、红树林或者沼泽地能为猛禽提供掩护的植被。", "title": "松鼠猴" }, { "docid": "1094725#7", "text": "紅大袋鼠喜歡吃草及其他植被。牠們可以一段長時間不用喝水,因牠們在吃綠色植物時吸收所需的水份。", "title": "紅大袋鼠" }, { "docid": "528100#4", "text": "松鼠猴花在觅食上的时间,跟食物的种类有关。如果能轻松找到较大的水果,松鼠猴就不会花太多时间觅食。否则,松鼠猴就会耗费大量时间寻找食物。觅食也是松鼠猴玩耍的过程,如果它们被捕获,就很容易感到无聊,因为食物直接就被提供了。 松鼠猴采用一夫多妻制,一个群体内部有多个雄性,多个雌性。大部分的社会行为是在不同的年龄/性别阶层中发生的,成年雄性、母子、青年中都有这样的阶层划分。群体的核心是由成年雌性及其幼崽组成的。每个阶层对成年雌性的吸引力最终使若干个阶层成为一个社会群体。青年成员活动频繁时,会在为数众多的成员周围玩耍嬉戏,但它们通常都围绕在成年雌性周围。至于成年雄性对雌性的吸引程度,则依赖每年的繁殖周期,雄性和雌性之间的距离与周期相关。整体上,不同阶层之间的交互大多时间与成年雌性有关。值得一提的是,松鼠猴内部的年龄/性别阶层划分并没有严格定义,因为性别之间的隔离程度有所不同。有些亚种之间的两性异形程度很高,因而是性别隔离的,雄性和雌性之间的交互较少,还有些亚种之间的两性异形程度低,两性之间是相容的。", "title": "松鼠猴" }, { "docid": "244527#21", "text": "诸如乾燥的猫尾草等新鲜的干草对豚鼠的健康有益,它们的食用粪球所含的营养来自猫尾草。同时,苜蓿也是一个不错的选择;大部分豚鼠非常喜欢吃苜蓿,而且食量惊人,不过给成年豚鼠喂食这种植物是否合适存在一些争议。有些宠物饲养者和兽医建议,喂食豆类植物效果更佳,苜蓿可能导致肥胖,除了怀孕的母猪和幼年小猪外, 其他豚鼠會從苜蓿吸收过多的钙而患上膀胱结石。不过,苜蓿草能够为它们补充蛋白质、氨基酸和纤维素。", "title": "豚鼠" }, { "docid": "3621073#3", "text": "主要食用由樹葉和果實,但也有時也會食用昆蟲和鳥蛋。大蕉松鼠有時會破開樹枝並抓食當中所含有的螞蟻幼蟲。牠們亦可進食體積比牠們身體大得多的水果,如芒果、菠蘿蜜、椰子等。牠們非常快速和敏捷,能在樹與樹之間跳上幾米,一般很少在地面上遊蕩。", "title": "大蕉松鼠" }, { "docid": "980005#12", "text": "紅背松鼠猴是雜食性的,主要吃昆蟲及其幼蟲、蜘蛛、果實、葉子、樹皮、花朵及花蜜。牠們也會吃細小的脊椎動物,如蝙蝠、鳥類、蜥蜴及青蛙。牠們會在森林的中至低層覓食,即40-50呎高。牠們每天約有三分之二至四分之三的時間來吃東西。在雨季由於節肢動物較少,牠們很難找到想吃的食物。", "title": "紅背松鼠猴" }, { "docid": "980005#14", "text": "紅背松鼠猴會幫助一些花朵散播種子及花粉。雖然牠們並非農業上重大的害蟲,但有時也會吃穀物、咖啡、香蕉及芒果。牠們也會吃豆莢、無花果及腰果等。", "title": "紅背松鼠猴" } ]
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2792213#0
东京有哪些特色温泉?
[ { "docid": "3458952#0", "text": "别府温泉位于日本九州东北部大分县别府市,自奈良时代起该地便是日本著名的“温泉之乡”。别府的温泉种类及其繁多,并且涌出量居世界第二,仅次于美国黄石国家公园。别府众多温泉中以七大地狱温泉最为著名,分别为:海地狱、鬼石坊主地狱、灶地狱、鬼山地狱、白池地狱、血之池地狱(血池地狱)、龙卷地狱。", "title": "别府温泉" } ]
[ { "docid": "847518#0", "text": "重庆市东温泉风景区包括重庆秀泉映月花园酒店、叁峰温泉、威特卡斯、航空温泉、天体温泉、热洞等一系列温泉及风景区。位于重庆市巴南区东泉镇境内五布河畔,这一地区距重庆市区约68公里,因位于重庆市区东面而得名。", "title": "重庆东温泉" }, { "docid": "847518#1", "text": "景区是由仙女峰、送子峰和飞英峰组成的自然景区。景区景点名称:大佛圣水、古佛洞、打儿洞、仙女洞、飞鹰峰、仙女峰、送子峰、飞仙谷、金镂玉衣、信号台、书山古寨、古佛清泉、瀑布水车(曲桥通幽)、古佛栈道、绝壁栈道。更有很多美丽的传说为东泉披上了神秘的文化色彩。比如:《裸浴的传说》传说远古的巴国时,有一猎户依山而居。一日,父亲进山打猎,忽闻小孩子哭喊声,循声而去,只见一大灰狼叼着小孩子向深山跑去。父亲疾步快抢,正中狼腹,恼怒的大灰狼丢下小孩扑向父亲,父亲和大灰狼一起掉进了万丈深渊。噩耗传来,悲痛欲绝的母亲哭瞎了双眼。十三岁的山崽每日背着母亲翻山赵岭,寻遍名医名药,终不痊愈。一天晚上,疲惫的山崽合衣而卧,睡梦中山神爷爷飘然而至:小山崽,你的孝顺感动了神灵,如来佛祖已将五步河水点化为“圣水”,每日背着母亲到五步河赤身浸泡吧,你母亲就能重见光明了。翌日,山崽就背着母亲到五步河浸泡温泉。一日复一日,冬去春来,从不间断,终于温泉“圣水”使山崽的母亲重见光明。从此,沐浴五步河水能消除病魔,逢凶化吉传遍方圆百里,村村户户,老老少少都纷纷到五步河裸体泡温泉。东泉裸浴就此传承至今。", "title": "重庆东温泉" }, { "docid": "847518#3", "text": "景区内有大小常温泉眼48处,主泉日流量2万立方米。温泉位于热洞内,水温约40℃,最高可达58℃,含氡、氟等微量元素,硫酸盐含量高,有一定医用疗效,并可制成矿泉水。", "title": "重庆东温泉" }, { "docid": "1888237#14", "text": "东汤镇温泉资源得天独厚。东汤温泉发现于唐朝,距今已有1300多年的历史。温泉水的日涌出量达2900余吨,水温高达78℃,以其水疗效果极佳享有盛名。清乾隆皇帝曾亲笔御书“圣泉第一”,当地百姓修筑庙宇圣泉寺以示纪念,并在庙门以“圣泉第一”为横额配成了一幅绝妙的对联,上联为“人间圣泉独一处”,下联为“世上神水无二家”。", "title": "东汤镇" }, { "docid": "97188#37", "text": "青森縣內溫泉度假地眾多,著名的有古牧溫泉、、等地。酸湯溫泉是日本第一個獲得國民保養溫泉地稱號的溫泉。位於青森市郊區的淺蟲溫泉因交通便利而遊客較多,有「東北的熱海」之稱。弘前城是日本十二現存天守之一,也是東北地方唯一的現存天守。弘前公園擁有日本最古的染井吉野櫻,擁有超過2600株櫻花。每年春季的是青森縣最大的觀光活動之一。秋季的弘前公園舉辦有,呈現出和春季截然不同的風貌", "title": "青森縣" }, { "docid": "304084#9", "text": "千山曾经是1987年版电视剧《红楼梦》,还有电影《古刹钟声》的重要外景地。歌曲《木鱼石的传说》的渊源也来自千山的木鱼石。千山温泉在千山正门以北约两公里处,(乘8路温泉站下车)此处建有多家假日酒店,这里的浴池、游泳馆以及所有客房的热水均来自地下的温泉。千山温泉出水温度高,对关节炎和皮肤病有一定治疗功效。", "title": "千山景区" }, { "docid": "78578#24", "text": "恩平地热资源蕴厚,富有温泉资源。经地质探查,蕴藏量较大的温泉有四处:良西的龙山月水村、松柏根黑泥村、大田的牛栏屋村、那吉的热水朗村。每处泉眼5~8个,流量10~20立方米/秒,温度有的高达70~80摄氏度。有帝都温泉、金山温泉、锦江温泉、山泉湾温泉、泉林水禾田温泉、恒大泉都等。", "title": "恩平市" }, { "docid": "847518#2", "text": "景区内有孙中山大元帅府秘书长杨沧白陵园,复旦大学战时校址。附近民众有东温泉中露天裸浴的习俗。近期有视频显示,香港著名演员汤镇宗曾到景区附近寺庙进香。", "title": "重庆东温泉" }, { "docid": "1059308#0", "text": "東京熱()是一家在美國註冊的著名日本成人電影製作商,成立於2003年。影片均为高清無碼影片。官方网站声明其内容是为包括220万日裔美国人在内的美国公众服务。其出品的内容主要偏硬調色情,涉及潮吹、無套性交、體內射精、顏射、口交、群交甚至性虐待等。因日本成人影片市場浮濫過度,東京熱在2010年的市場銷售量比2009年減少了15%。2015年其网站推出繁体中文界面。2018年起已不再推出新电影,网站转为销售旧片集锦及其它公司电影。", "title": "东京热" } ]
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5544144#0
缅甸盛产哪些水果?
[ { "docid": "6291808#13", "text": "從其他國家引種的熱帶水果有來自印度的龍眼、來自非洲的西瓜、來自中國的柿子、來自拉丁美洲的酪梨、釋迦、鳳梨、芭樂、木瓜、人心果、百香果。有些水果有季節性,有些水果則一年四季都有,如香蕉、西瓜、鳳梨、木瓜。", "title": "印尼飲食" }, { "docid": "181223#7", "text": "在密支那附近出产的香米称作\"khat cho\",被认为是缅甸最好的香米。密支那是翡翠的重要产地。密支那亦因其水果而出名,包括菠萝,西瓜,荔枝和牛奶果。", "title": "密支那" }, { "docid": "3952587#5", "text": "其他受歡迎的熱帶水果,包括山竹、菠蘿蜜、龍眼、荔枝、紅毛丹、和鳳梨。有些水果也被當用作其他菜肴的原料,如:冰镇甜品、糖醋​​猪肉、以及某些类型的蔬果沙拉,如囉喏。", "title": "新加坡飲食" } ]
[ { "docid": "26508#57", "text": "緬甸盛產稻米,人民以大米為主食。早餐常吃魚湯麵、椰子麵、椰子粥、涼拌麵、涼拌米粉及用糯米、椰子、白糖做的各種各樣的糕點小吃。", "title": "缅甸" }, { "docid": "21908#49", "text": "老挝亦盛产热带水果,芒果年产量1万至2万吨,老挝人称之为“果中之王”;葡萄柚是老挝名产水果,年产量2至3万吨;木瓜为高产水果,年产量超过10万吨。此外,万象地区特产檀香;安息香则是老挝主要特产,产量占世界总量的70%,用于化工和医药原料,年产量达50余吨。按照人均占有量计算,老挝为东南亚禽畜最多的国家之一,全国有150多万公顷天然牧场,民间畜禽养殖历史悠久,几乎每家每户都从事家畜和家禽饲养。老挝林业资源丰富,森林面积达到1,400万至1,500万公顷,但木材蓄积量因森林砍伐等问题逐年减少。由于工业基础薄弱,老挝的林业资源开发程度并不高。", "title": "老挝" }, { "docid": "834952#5", "text": "緬甸盛產稻米,人民以大米為主食。早餐常吃魚湯麵、椰子麵、椰子粥、涼拌麵、涼拌米粉及用糯米、椰子、白糖做的各種各樣的糕點小吃。", "title": "缅甸文化" }, { "docid": "1050749#26", "text": "广东水果资源十分丰富,是中国著名的水果之乡,广东作为经济作物栽培的水果品种有四、五十种之多,主要有柑桔、荔枝、龙眼、柚类、芒果、香蕉、菠萝等,2004年全省水果面积986.65千公顷,总产量787.85万吨。按产量分,茂名和湛江和水果出产地,水果年产均在200万吨左右。按种类分,肇庆为柑橘主产地,2009年年产74万多吨。茂名和湛江为热带水果出产地,香蕉年产均在百万吨以上;湛江为菠萝主产地,年产过50万吨;茂名为荔枝和龙眼主产地,荔枝年产均在30万吨以上,龙眼年产在20万吨以上。", "title": "广东省经济" }, { "docid": "70090#62", "text": "普宁素来有“水果之乡”之称,水果计有30科64种286个品种,具体种植品种与地势息息相关,榕江南岸冲击平原和北部丘陵以种植蕉柑为主,辅以荔枝、香蕉、油甘、青榄、青梅等;中部平原丘陵区以发展青榄为主,辅以蕉柑、青梅、龙眼、油甘等;西南部山地丘陵以发展青梅和优质茶为主,辅以青榄、菠萝、油甘、荔枝。普宁的水果除销鲜外,为提升其附加价值,大部分会用于加工。青梅、蕉柑、青榄、油甘、为普宁主要的大宗传统水果。", "title": "普宁市" }, { "docid": "509#17", "text": "大连地区盛产苹果、梨、桃等水果,沿海地区盛产海参、鲍鱼、牡蛎、对虾及各种鱼类。黑龙江省的三江平原是中国第二大的稻米生产基地。", "title": "中国东北地区" }, { "docid": "6291808#12", "text": "原產於印尼的熱帶水果有:芒果、香蕉、椰子、山竹、榴槤、蓮霧、蘭撒、柚子、红毛丹、榴槤蜜、菠蘿蜜、太平洋桲。", "title": "印尼飲食" } ]
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986470#0
四川美食有哪些?
[{"docid":"17677#28","text":"四川各地小吃通常也被看作是川菜的组成部分。由于(...TRUNCATED)
[{"docid":"5496609#3","text":"本站所在的“一品天下”为成都打造的美食一条街,(...TRUNCATED)
[0.13579730689525604,0.5400390625,-0.26092529296875,0.20736083388328552,0.054367829114198685,-0.1666(...TRUNCATED)

MIRACL (zh) embedded with cohere.ai multilingual-22-12 encoder

We encoded the MIRACL dataset using the cohere.ai multilingual-22-12 embedding model.

The query embeddings can be found in Cohere/miracl-zh-queries-22-12 and the corpus embeddings can be found in Cohere/miracl-zh-corpus-22-12.

For the orginal datasets, see miracl/miracl and miracl/miracl-corpus.

Dataset info:

MIRACL 🌍🙌🌏 (Multilingual Information Retrieval Across a Continuum of Languages) is a multilingual retrieval dataset that focuses on search across 18 different languages, which collectively encompass over three billion native speakers around the world.

The corpus for each language is prepared from a Wikipedia dump, where we keep only the plain text and discard images, tables, etc. Each article is segmented into multiple passages using WikiExtractor based on natural discourse units (e.g., \n\n in the wiki markup). Each of these passages comprises a "document" or unit of retrieval. We preserve the Wikipedia article title of each passage.

Embeddings

We compute for title+" "+text the embeddings using our multilingual-22-12 embedding model, a state-of-the-art model that works for semantic search in 100 languages. If you want to learn more about this model, have a look at cohere.ai multilingual embedding model.

Loading the dataset

In miracl-zh-corpus-22-12 we provide the corpus embeddings. Note, depending on the selected split, the respective files can be quite large.

You can either load the dataset like this:

from datasets import load_dataset
docs = load_dataset(f"Cohere/miracl-zh-corpus-22-12", split="train")

Or you can also stream it without downloading it before:

from datasets import load_dataset
docs = load_dataset(f"Cohere/miracl-zh-corpus-22-12", split="train", streaming=True)

for doc in docs:
    docid = doc['docid']
    title = doc['title']
    text = doc['text']
    emb = doc['emb']

Search

Have a look at miracl-zh-queries-22-12 where we provide the query embeddings for the MIRACL dataset.

To search in the documents, you must use dot-product.

And then compare this query embeddings either with a vector database (recommended) or directly computing the dot product.

A full search example:

# Attention! For large datasets, this requires a lot of memory to store
# all document embeddings and to compute the dot product scores.
# Only use this for smaller datasets. For large datasets, use a vector DB

from datasets import load_dataset
import torch

#Load documents + embeddings
docs = load_dataset(f"Cohere/miracl-zh-corpus-22-12", split="train")
doc_embeddings = torch.tensor(docs['emb'])

# Load queries 
queries = load_dataset(f"Cohere/miracl-zh-queries-22-12", split="dev")

# Select the first query as example
qid = 0
query = queries[qid]
query_embedding = torch.tensor(queries['emb'])

# Compute dot score between query embedding and document embeddings
dot_scores = torch.mm(query_embedding, doc_embeddings.transpose(0, 1))
top_k = torch.topk(dot_scores, k=3)

# Print results
print("Query:", query['query'])
for doc_id in top_k.indices[0].tolist():
    print(docs[doc_id]['title'])
    print(docs[doc_id]['text'])

You can get embeddings for new queries using our API:

#Run: pip install cohere
import cohere
co = cohere.Client(f"{api_key}")  # You should add your cohere API Key here :))
texts = ['my search query']
response = co.embed(texts=texts, model='multilingual-22-12')
query_embedding = response.embeddings[0] # Get the embedding for the first text

Performance

In the following table we compare the cohere multilingual-22-12 model with Elasticsearch version 8.6.0 lexical search (title and passage indexed as independent fields). Note that Elasticsearch doesn't support all languages that are part of the MIRACL dataset.

We compute nDCG@10 (a ranking based loss), as well as hit@3: Is at least one relevant document in the top-3 results. We find that hit@3 is easier to interpret, as it presents the number of queries for which a relevant document is found among the top-3 results.

Note: MIRACL only annotated a small fraction of passages (10 per query) for relevancy. Especially for larger Wikipedias (like English), we often found many more relevant passages. This is know as annotation holes. Real nDCG@10 and hit@3 performance is likely higher than depicted.

Model cohere multilingual-22-12 nDCG@10 cohere multilingual-22-12 hit@3 ES 8.6.0 nDCG@10 ES 8.6.0 acc@3
miracl-ar 64.2 75.2 46.8 56.2
miracl-bn 61.5 75.7 49.2 60.1
miracl-de 44.4 60.7 19.6 29.8
miracl-en 44.6 62.2 30.2 43.2
miracl-es 47.0 74.1 27.0 47.2
miracl-fi 63.7 76.2 51.4 61.6
miracl-fr 46.8 57.1 17.0 21.6
miracl-hi 50.7 62.9 41.0 48.9
miracl-id 44.8 63.8 39.2 54.7
miracl-ru 49.2 66.9 25.4 36.7
Avg 51.7 67.5 34.7 46.0

Further languages (not supported by Elasticsearch):

Model cohere multilingual-22-12 nDCG@10 cohere multilingual-22-12 hit@3
miracl-fa 44.8 53.6
miracl-ja 49.0 61.0
miracl-ko 50.9 64.8
miracl-sw 61.4 74.5
miracl-te 67.8 72.3
miracl-th 60.2 71.9
miracl-yo 56.4 62.2
miracl-zh 43.8 56.5
Avg 54.3 64.6
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