import spacy
nlp = spacy.load('en')

text_list = []
text_list.append("I have spent 5+ years developing bug-tracking systems and creating data managing systems.")
text_list.append("I have spent 2+ years in analysis and implementation of complex, custom-built applications.")

for content in text_list:
    document = nlp(content)
    sentences = [sent for sent in document.sents if('year') in sent.string.lower()]
    for s in sentences:
        for ent in nlp(s.text).ents:
            if ent.label_ == "DATE":
                if('year' in ent.text):
                    s_text = nlp(ent.text)
                    num_list = []
                    print("nText with Number::", s_text)
                    for word in s_text:
                        print("Word :", word, "  Pos :", word.pos_, "  Tag :",  word.tag_, "  Like Num? :",  word.like_num)

Text with Number:: 5+ years
Word : 5   Pos : NUM   Tag : CD   Like Num? : True
Word : +   Pos : SYM   Tag : SYM   Like Num? : False
Word : years   Pos : NOUN   Tag : NNS   Like Num? : False

Text with Number:: 2+ years
Word : 2   Pos : PUNCT   Tag : LS   Like Num? : True
Word : +   Pos : SYM   Tag : SYM   Like Num? : False
Word : years   Pos : NOUN   Tag : NNS   Like Num? : False