我有一个类似于以下内容的数据集
[[(Sky proposal, is, matter), (Sky proposal, is, Mays spokesman)], [(Women,
lag, Intel report)], [(Amazon, expected, to unveil)], [(Goldman Sachs, raising,
billion)], [(MHP, opens, books)], [(Disney, hurls, magic), (Disney, hurls,
moolah)], [(Amazon, offering, loans), (Amazon, offering, to)], [(JPMorgan,
seeks, billion), (JPMorgan, seeks, WaMu claims)], [(Comcast, accuses,
Discovery)], [(Boeing, sees, sales)], [(BRIEFNetflix Inc, reports, earnings)],
[(Broadcom deal, may stunt, Valley investment)], [(Apple, sell, iPads)], [(oil,
pull, Street)], [(Fed, tells, Goldman), (Fed, tells, to improve)], [(ideas,
undermine, Brexit), (ideas, undermine, Facebook)], [(FX DEBTC, hits, low),
(tumbles investors, buy, greenbacks)], [(BRIEFWells Fargo, announces, plan)],
[(Red Hat, jumps, IBM shares dip)], [(Nasdaqs tech focus, helps, drive)],
[(Amazon, offers, music service)], [(EXCLUSIVEFormer risk chief, warned,
Bank)], ...
我正在尝试使用Spacy将每个元组转换为向量空间（词嵌入），但是，我一直在努力寻找可以迭代并提供每个元组的向量输出的实现
我正在尝试通过以下功能使用
import Spacy
doc = nlp("NLP project test")
doc.vector