Corpus based classification of text in Australian contracts

Written contracts are a fundamental framework for commercial and cooperative transactions and relationships. Limited research has been published on the application of machine learning and natural language processing (NLP) to contracts. In this paper we report the classification of components of contract texts using machine learning and hand-coded methods. Authors studying a range of domains have found that combining machine learning and rule based approaches increases accuracy of machine learning. We find similar results which suggest the utility of considering leveraging hand coded classification rules for machine learning. We attained an average accuracy of 83.48% on a multiclass labelling task on 20 contracts combining machine learning and rule based approaches, increasing performance over machine learning alone

Construction contract risk identification based on knowledge-augmented language model

Contract review is an essential step in construction projects to prevent potential losses. However, the current methods for reviewing construction contracts lack effectiveness and reliability, leading to time-consuming and error-prone processes. While large language models (LLMs) have shown promise in revolutionizing natural language processing (NLP) tasks, they struggle with domain-specific knowledge and addressing specialized issues. This paper presents a novel approach that leverages LLMs with construction contract knowledge to emulate the process of contract review by human experts. Our tuning-free approach incorporates construction contract domain knowledge to enhance language models for identifying construction contract risks. The use of a natural language when building the domain knowledge base facilitates practical implementation. We evaluated our method on real construction contracts and achieved solid performance. Additionally, we investigated how large language models employ logical thinking during the task and provide insights and recommendations for future research

Evaluation of construction contract documents to be applied in modular construction focusing ambiguities; A text processing approach

Modular coordination in building construction has become increasingly popular, particularly in Northern Europe and North America. In Canada, modular construction came to considerable attention over the last decade due to its valuable effect on project constraints, safety, and preventing construction and demolition waste. However, the modular construction industry still adopts the same administrative procedures designed for the conventional construction industry, even though the features of modular and conventional construction are different in terms of construction processes and methods. Due to this trend, ambiguities in administrative documents are widely occurred and are one of the main causes to generate conflict, disputes, and claims between owners and modular suppliers as general contractors. As a first step in the this research to overcome this challenge, the research team focuses on investigating the contents and structures of the current standard contracts and modular RFPs, which are one of the major sources of confusion in modular construction, in order to mitigate and/or remove the ambiguities based on the considering the specifications of off-site construction procedures and system. In this case, this research illustrates a conceptual framework that has two parts: First, classification of the main sources of ambiguities in construction contracts (both Conventional and modular) and second, to identify the similarities and differences between Canadian documents (standard contracts and modular RFPs) and benchmark countries by applying through text processing and readability analysis. We applied text processing to find top terms, including terms with high frequency (TF) in each document, also high TF-IDF terms, which species occur in one document and not others then, we detected manually the three standard contracts and four RFPs and compare them with the output of literature review to identify the major issues that are common. The readability analysis shows the textual complexity of a document and to what extent the documents are difficult to read. The main findings indicate that the modular industry in Canada suffers from a lack of specific standard contract documents for modular construction

Doing Business in the Philippines

[Excerpt] The Philippines which lies at the heart of Southeast Asia is a viable place for doing business.The country’s economy continues to grow despite the unabated political noise. The Philippine Peso ended 2005 as the best performer in Asia, with a 6.01 percent gain for the year, boosted by hefty inflows of remittances from Filipinos working overseas and optimism about the government’s fiscal reform program and lower yields at the regular treasury bill auction. The Philippine Stock Exchange, on the other hand, registered the second fastest growth rate in Southeast Asia in 2005. The Philippine Composite Index (Phisix) went up by 14.99 percent last year, trailing the Jakarta Composite Index of Indonesia which went up 16.24 percent. The Filipino workforce is another key advantage of the Philippines.The literacy rate in the country is among the highest in the region and around 350,000 highly trainable graduates add to the professional pool every year. On the political front, the Philippine government has been working on the proposal to change the present presidential system to a parliamentary-federal form of government through a charter change, in order to fast track the enactment of legislative measures and the delivery of public services to the provinces. The 1987 Constitution provides for a presidential system of government with a bicameral Congress