The Penn Treebank project has recently introduced a new syntactic annotation scheme to highlight predicate-argument structure. This paper discusses the implementation of key aspects of this new scheme, which includes: 1. **Consistent Treatment of Grammatical Phenomena**: Ensuring that similar grammatical phenomena are represented consistently. 2. **Null Elements**: Introducing null elements for phenomena like wh-movement, passive, and infinitival subjects, co-indexed with lexical material. 3. **Non-Context Free Annotational Mechanism**: Providing a method to easily recover the structure of discontinuous constituents. 4. **Clear Distinction Between Verb Arguments and Adjuncts**: Offering a clear tagging system for semantic roles, with notational devices for ambiguous cases. The new scheme aims to improve the consistency and richness of the annotation, making it more useful for parser evaluation, automatic parser training, and linguistic research. The paper also details the implementation of these aspects, including the use of null elements, pseudo-attachment, and notational devices to handle conjoined structures and gapping. The goal is to create a corpus that can serve as a gold standard for various linguistic and computational tasks.The Penn Treebank project has recently introduced a new syntactic annotation scheme to highlight predicate-argument structure. This paper discusses the implementation of key aspects of this new scheme, which includes: 1. **Consistent Treatment of Grammatical Phenomena**: Ensuring that similar grammatical phenomena are represented consistently. 2. **Null Elements**: Introducing null elements for phenomena like wh-movement, passive, and infinitival subjects, co-indexed with lexical material. 3. **Non-Context Free Annotational Mechanism**: Providing a method to easily recover the structure of discontinuous constituents. 4. **Clear Distinction Between Verb Arguments and Adjuncts**: Offering a clear tagging system for semantic roles, with notational devices for ambiguous cases. The new scheme aims to improve the consistency and richness of the annotation, making it more useful for parser evaluation, automatic parser training, and linguistic research. The paper also details the implementation of these aspects, including the use of null elements, pseudo-attachment, and notational devices to handle conjoined structures and gapping. The goal is to create a corpus that can serve as a gold standard for various linguistic and computational tasks.