As a helpful and smart assistant, your task is to parse a given text in any language to Universal Dependency (UD) format including POS tags and dependency relations (HEAD and DEPREL).
Key Components of UD Annotation:
1. Tokens: The fundamental units within UD are tokens. These can be individual words, punctuation marks, or even parts of multi-word expressions. Each token has several associated attributes.
2. UPOS Tags: The UPOS field in the CoNLL-U format represents the universal part-of-speech tag assigned to each word. This tag is part of a universal POS tag set designed to be applicable across different languages. The UPOS tags include categories such as NOUN, VERB, ADJ (adjective), ADV (adverb), PRON (pronoun), DET (determiner), and more. 
3. Dependency Relations: Dependency relations are the core of the syntactic representation. They form a tree structure over the tokens in a sentence. Here's how they work:
    - HEAD: This field indicates the head of the current word. The head is the word that the current word is connected to in the dependency parse tree. The value is an integer that corresponds to the ID of the head word within the same sentence. A value of zero (0) indicates that the word is the root of the sentence.
    - DEPREL: The DEPREL field specifies the type of dependency relation between the current word and its head (as specified in the HEAD field). The value is a universal dependency relation or a language-specific subtype of such a relation.
Note: Blank lines are used to mark the boundaries between sentences.
Example:
Let's analyze this sentence with its UD annotation:
"The big dog chased the cat."
1. Tokenization:
- The
- big
- dog
- chased
- the
- cat
- .
2. UPOS Tags:
- The: DET
- big: ADJ
- dog: NOUN
- chased: VERB
- the: DET
- cat: NOUN
- .: PUNCT
3. Head node (parent):
- The: the parent of this word is "dog" at position 3
- big: the parent of this word is "dog" at position 3
- dog: the parent of this word is "chased" at position 4
- chased: this is the root node, therefore its head is 0
- the: the parent of this word is "cat" at position 6
- cat: the parent of this word is "chased" at position 4
- .: the parent of this word is "chased" at position 4
3. Dependency Relations:
- root(ROOT, chased)
- det(dog, The)
- amod(dog, big)
- nsubj(chased, dog)
- det(cat, the)
- obj(chased, cat)
Combining the above annotations, the final output in UD format is:
Position	Tokenization	UPOS	Head	Deprel
1	The	DET	3	det
2	big	ADJ	3	amod
3	dog	NOUN	4	nsubj
4	chased	VERB	0	ROOT
5	the	DET	6	det
6	cat	NOUN	4	obj
7	.	PUNCT	4	punct
Generate UD annotations for the following tokenized text:
Let me put it this way - If you have watched TV recently, crossed a modern bridge, flown in an airplane, recieved any form of modern medicine, did any mathematics, drove a car, used a cellular phone, etc. then you have somehow directly reaped the rewards which NASA has returned to us.
Postion	Tokenization
1	Let
2	me
3	put
4	it
5	this
6	way
7	-
8	If
9	you
10	have
11	watched
12	TV
13	recently
14	,
15	crossed
16	a
17	modern
18	bridge
19	,
20	flown
21	in
22	an
23	airplane
24	,
25	recieved
26	any
27	form
28	of
29	modern
30	medicine
31	,
32	did
33	any
34	mathematics
35	,
36	drove
37	a
38	car
39	,
40	used
41	a
42	cellular
43	phone
44	,
45	etc.
46	then
47	you
48	have
49	somehow
50	directly
51	reaped
52	the
53	rewards
54	which
55	NASA
56	has
57	returned
58	to
59	us
60	.
Position	Tokenization	UPOS	Head	Deprel
1	Let	VERB	0	root
2	me	PRON	1	obj
3	put	VERB	1	xcomp
4	it	PRON	3	obj
5	this	DET	6	det
6	way	NOUN	3	obl:npmod
7	-	PUNCT	1	punct
8	If	SCONJ	11	mark
9	you	PRON	11	nsubj
10	have	AUX	11	aux
11	watched	VERB	51	advcl
12	TV	PROPN	11	obj
13	recently	ADV	11	advmod
14	,	PUNCT	15	punct
15	crossed	VERB	11	conj
16	a	DET	18	det
17	modern	ADJ	18	amod
18	bridge	NOUN	15	obj
19	,	PUNCT	20	punct
20	flown	VERB	11	conj
21	in	ADP	23	case
22	an	DET	23	det
23	airplane	NOUN	20	obl
24	,	PUNCT	25	punct
25	recieved	VERB	11	conj
26	any	DET	27	det
27	form	NOUN	25	obj
28	of	ADP	30	case
29	modern	ADJ	30	amod
30	medicine	NOUN	27	nmod
31	,	PUNCT	32	punct
32	did	VERB	11	conj
33	any	DET	34	det
34	mathematics	NOUN	32	obj
35	,	PUNCT	36	punct
36	drove	VERB	11	conj
37	a	DET	38	det
38	car	NOUN	36	obj
39	,	PUNCT	40	punct
40	used	VERB	11	conj
41	a	DET	43	det
42	cellular	ADJ	43	amod
43	phone	NOUN	40	obj
44	,	PUNCT	45	punct
45	etc.	X	11	conj
46	then	ADV	51	advmod
47	you	PRON	51	nsubj
48	have	AUX	51	aux
49	somehow	ADV	51	advmod
50	directly	ADV	51	advmod
51	reaped	VERB	1	parataxis
52	the	DET	53	det
53	rewards	NOUN	51	obj
54	which	PRON	57	obj
55	NASA	PROPN	57	nsubj
56	has	AUX	57	aux
57	returned	VERB	53	acl:relcl
58	to	ADP	59	case
59	us	PRON	57	obl
60	.	PUNCT	1	punct