# Syntactic structures and the general Markov models

arXiv: https://arxiv.org/abs/2104.08462 · HTML: https://mlsanity.com/paper/2104.08462/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 68 references that are in the map.
- First posted on arXiv 17 Apr 2021.

## Builds on (most cited first, 7 of 7)

- [Topological Analysis of Syntactic Structures](https://mlsanity.com/paper/1903.05181/) (2019)
- [Persistent Topology of Syntax](https://mlsanity.com/paper/1507.05134/) (2015)
- [Syntactic Structures and Code Parameters](https://mlsanity.com/paper/1610.00311/) (2016)
- [Heat Kernel analysis of Syntactic Structures](https://mlsanity.com/paper/1803.09832/) (2018)
- [Prevalence and recoverability of syntactic parameters in sparse distributed memories](https://mlsanity.com/paper/1510.06342/) (2015)
- [Syntactic Phylogenetic Trees](https://mlsanity.com/paper/1607.02791/) (2016)
- [Phylogenetics of Indo-European Language families via an Algebro-Geometric Analysis of their Syntactic Structures](https://mlsanity.com/paper/1712.01719/) (2017)

## Built on by (most cited first, 1 of 1)

- [Mathematical Structure of Syntactic Merge](https://mlsanity.com/paper/2305.18278/) (2023)

## Abstract (arXiv)

We study phylogenetic signal present in syntactic information by considering the syntactic structures data from Longobardi (2017b), Collins (2010), Ceolin et al. (2020) and Koopman (2011). Focusing first on the general Markov models, we explore how well the the syntactic structures data conform to the hypothesis required by these models. We do this by comparing derived phylogenetic trees against trees agreed on by the linguistics community. We then interpret the methods of Ceolin et al. (2020) as an infinite sites evolutionary model and compare the consistency of the data with this alternative. The ideas and methods discussed in the present paper are more generally applicable than to the specific setting of syntactic structures, and can be used in other contexts, when analyzing consistency of data with against hypothesized evolutionary models.