# What is the intuition behind the rules of Hobbs Algorithm?

I am trying to understand the Hobbs Algorithm. I am able to follow the algorithm and solve tree walking questions to find the antecedent of a pronoun, but I do not get the intuition behind the rules defined in the Hobbs Algorithm. Can someone please help me in explaining the meaning of these rules ?

1. Begin at the noun phrase (NP) node immediately dominating the pronoun.

2. Go up the tree to the first NP or sentence (S) node encountered. Call this node X, and call the path used to reach it p.

3. Traverse all branches below node X to the left of path p in a left-to-right, breadth-first fashion. Propose as the antecedent any NP node that is encountered which has an NP or S node between it and X.

4. If node X is the highest S node in the sentence, traverse the surface parse trees of previous sentences in the text in order of recency, the most recent first; each tree is traversed in a left-to-right, breadth-first manner, and when an NP node is encountered, it is proposed as antecedent.If X is not the highest S node in the sentence, continue to step 5.

5. From node X, go up the tree to the first NP or S node encountered. Call this new node X, and call the path traversed to reach it p.

6. If X is an NP node and if the path p to X did not pass through the Nominal node that X immediately dominates, propose X as the antecedent.

7. Traverse all branches below node X to the left of path p in a left-to-right, breadth- first manner. Propose any NP node encountered as the antecedent.

8. If X is an S node, traverse all branches of node X to the right of path p in a left-to- right, breadth-first manner, but do not go below any NP or S node encountered. Propose any NP node encountered as the antecedent.

9. Go to Step4

I have taken these rules from Jurafsky & Martin. These rules can also be found in this paper .

• It looks like a step-by-step reconstruction of Langacker's dictum that a pronoun may not both precede and command its antecedent, with a metric for closeness. – jlawler Apr 17 '18 at 2:26