do all open predicates need to be targets?

[pli...@gmail.com]

I'm currently doing some experiments with a small PSL model for named entity recognition. The current idea is to start with the results from an existing named entity recogniser (e.g. from Spacy) but add a constraint stating that the labels should be consistent across a document (to make sure "London" is not labelled "LOC" somewhere in the document and "ORG" somewhere else).

Here's my model:

# For each entity E, the label probabilities should sum to 1
EntityLabel(E, +Label) = 1.

# Transfer the label outputs from Spacy to the EntityLabel predicate
2: EntityLabel_Spacy(E, Label) -> EntityLabel(E, Label) ^2

# We define a predicate DocLevelLabel expressing the distribution of labels for a given text chunk, such as "London"
DocLevelLabel(Text, Label) = 1/|E| EntityLabel(+E, Label). {E: EntityText(E, Text)}

# We add a soft constraint to increase the probability of consistent labels
1: DocLevelLabel(Text, Label) & EntityText(E, Text) -> EntityLabel(E, Label) ^2

Here's my data file:

predicates:
EntityLabel/2: open
DocLevelLabel/2: open
EntityLabel_Spacy/2: closed
EntityText/2: closed

observations:
EntityLabel_Spacy : EntityLabel_Spacy_obs.txt
EntityText : EntityText_obs.txt

targets:
EntityLabel : EntityLabel_targets.txt

With this data file, the label consistency constraint does not seem to work unfortunately. But if I also add DocLevelLabel as a target in the data file, the problem strangely disappears.

So here's my question: do all open predicates need to be explicitly specified as targets, even though we are not interested in inferring their values (as is the case for DocLevelLabel, which is just a latent variable)?

[Eriq Augustine]

Hey,

The short answer is yes, you should explicitly specify all your inference targets.

This thread has a more complete answer:

https://groups.google.com/d/msg/psl-users/_NZitpkL9fQ/iMRzfzmsAQAJ

-eriq

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