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:
We will be targeting to raise at least $100,000 so company contributions will range from $10,000-$20,000 per person ($10k minimum per person) depending on the number of respondents.
Postion	Tokenization
1	We
2	will
3	be
4	targeting
5	to
6	raise
7	at
8	least
9	$
10	100,000
11	so
12	company
13	contributions
14	will
15	range
16	from
17	$
18	10,000
19	-
20	$
21	20,000
22	per
23	person
24	(
25	$
26	10
27	k
28	minimum
29	per
30	person
31	)
32	depending
33	on
34	the
35	number
36	of
37	respondents
38	.
Position	Tokenization	UPOS	Head	Deprel
1	We	PRON	4	nsubj
2	will	AUX	4	aux
3	be	AUX	4	aux
4	targeting	VERB	0	root
5	to	PART	6	mark
6	raise	VERB	4	xcomp
7	at	ADV	8	case
8	least	ADV	9	nmod
9	$	SYM	6	obj
10	100,000	NUM	9	compound
11	so	ADV	15	mark
12	company	NOUN	13	compound
13	contributions	NOUN	15	nsubj
14	will	AUX	15	aux
15	range	VERB	4	advcl
16	from	ADP	17	case
17	$	SYM	15	obl
18	10,000	NUM	15	nummod
19	-	SYM	20	case
20	$	SYM	17	nmod
21	20,000	NUM	20	nummod
22	per	ADP	23	case
23	person	NOUN	17	nmod
24	(	PUNCT	28	punct
25	$	SYM	28	compound
26	10	NUM	25	compound
27	k	NUM	25	compound
28	minimum	NOUN	17	appos
29	per	ADP	30	case
30	person	NOUN	28	nmod
31	)	PUNCT	28	punct
32	depending	VERB	35	case
33	on	ADP	35	case
34	the	DET	35	det
35	number	NOUN	15	obl
36	of	ADP	37	case
37	respondents	NOUN	35	nmod
38	.	PUNCT	4	punct