# A DeBERTa-Based Semantic Conversion Model for Spatiotemporal Questions in Natural Language
## 4 Semantic Understanding Methods
### Semantic Parsing  
Building on question classification, semantic parsing was performed on intra-category questions by identifying the relationships among encoded entity elements to determine the query conditions for each type of question. In the context of geospatial and temporal questions, the focus was primarily on spatial relationships, temporal relationships, and dependency relationships [39]. The LTP (Language Technology Platform) tool [40] was used to perform dependency syntax analysis on the questions, and relationship recognition was carried out based on the needs and characteristics of different question types. 1. Spatial Relationships  
The three elements of spatial descriptions are the position object (P), the reference object (C), and the spatial relation (r) [41]. The position object is the core of the spatial description, representing the object being located or described. The reference object serves as the benchmark or reference point used to locate the position object within the spatial description, providing a reference framework for the position object. Spatial relations are the spatial connections between the position object and the reference object, including directional relationships (such as east, west, south, north, northeast, southeast, etc. ), distance relationships (such as around, nearby, etc. ), and topological relationships (such as bordering, containing, adjacent, etc.). The spatial relationship triplet in a question is represented in the following form:  
\[<P_{i},r_{j},C_{i}>_{j},i,j=1,2,\ \ldots,n \tag{7}\]  
In the formula, i represents all objects related to r in the question, and j represents all spatial relationships in the sentence. For example, in the sentence \"the park and bank north of the museum\", it contains \(<Park,North,Museum>_{1},\ <Bank,North, Museum \(>_{1}\), \(<Park,Nearby,Museum>_{2},\ <Bank,Nearby,Museum \(>_{2}\). Based on the semantic encoding results of the sentence, if there is a spatial relationship encoding r, then use a combination of dependency syntax and rule-based methods to identify the location object and reference object of the spatial relationship and determine the spatial relationship triple. 2. Temporal Relationships  
When describing geographic entities, temporal factors should be considered, such as the historical evolution of geographic entities, changing trends, and the state of specific periods [42], to more comprehensively understand and describe geographic phenomena and analyze the changes in geographic data over time. Spatiotemporal questions mainly include absolute time (e.g., September 2010) and relative time (e.g., five years ago). Their temporal relationship words mainly express temporal sequence relationships (e.g., before, after, until, etc.) and temporal modification relationships (e.g., around, about, approximately, etc.) [43]. In spatiotemporal questions, the queries and descriptions of time primarily focus on the time attributes of geographic entities or the temporal relationships between geographic entities. If a time encoding 'd' and a temporal relationship encoding 'r' are identified in the question, then time is assigned as an attribute or association to the entity encodings in the question, and 'r' is mapped to the temporal relationship function based on the temporal relationship set. 3. Dependency Relationships  
The entities in the question usually have dependency relationships, such as subject-predicate, verb-object, coordination, attribute modified, and preposition-object [44; 45]. For instance, if there is a coordination relationship among entities in the sentence and the first entity is associated with a certain relationship (such as a spatial relationship), then the coordinated entity is usually also associated with the same relationship. If the dependency relationship between entities is that of an attribute modifier, it indicates a modification relationship between the entities.