more updates to the README

README.md

@@ -79,23 +79,22 @@ The FICLE Dataset contains only English.
 
 ### Data Fields
 
-* `Claim (string)`:
-* `Context (string)`:
-* `Source (string)`:
-* `Source Indices (string)`:
-* `Relation (string)`:
-* `Relation Indices (string)`:
-* `Target (string)`:
-* `Target Indices (string)`:
-* `Inconsistent Claim Component (string)`:
-* `Inconsistent Context-Span (string)`:
-* `Inconsistent Context-Span Indices (string)`:
-* `Inconsistency Type (string)`:
-* `Fine-grained Inconsistent Entity-Type (string)`:
-* `Coarse Inconsistent Entity-Type (string)`:
+* `Claim (string)`: A statement or proposition relating to the consistency or inconsistency of certain facts or information.
+* `Context (string)`: The surrounding information or background against which the claim is being evaluated or compared. It provides additional details or evidence that can support or challenge the claim.
+* `Source (string)`: It is the linguistic chunk containing the entity lying to the left of the main verb/relating chunk. 
+* `Source Indices (string)`: Source indices refer to the specific indices or positions within the source string that indicate the location of the relevant information.
+* `Relation (string)`: It is the linguistic chunk containing the verb/relation at the core of the identified inconsistency.
+* `Relation Indices (string)`: Relation indices indicate the specific indices or positions within the relation string that highlight the location of the relevant information.
+* `Target (string)`: It is the linguistic chunk containing the entity lying to the right of the main verb/relating chunk. 
+* `Target Indices (string)`: Target indices represent the specific indices or positions within the target string that indicate the location of the relevant information.
+* `Inconsistent Claim Component (string)`: The inconsistent claim component refers to a specific linguistic chunk within the claim that is identified as inconsistent with the context. It helps identify which part of the claim triple is problematic in terms of its alignment with the surrounding information.
+* `Inconsistent Context-Span (string)`: A span or portion marked within the context sentence that is found to be inconsistent with the claim. It highlights a discrepancy or contradiction between the information in the claim and the corresponding context.
+* `Inconsistent Context-Span Indices (string)`: The specific indices or location within the context sentence that indicate the inconsistent span.
+* `Inconsistency Type (string)`:  The category or type of inconsistency identified in the claim and context.
+* `Fine-grained Inconsistent Entity-Type (string)`: The specific detailed category or type of entity causing the inconsistency within the claim or context. It provides a more granular classification of the entity associated with the inconsistency.
+* `Coarse Inconsistent Entity-Type (string)`: The broader or general category or type of entity causing the inconsistency within the claim or context. It provides a higher-level classification of the entity associated with the inconsistency.
   
 
-
 ### Data Splits
 The FICLE dataset comprises a total of 8,055 samples in the English language, each representing different instances of inconsistencies. 
 These inconsistencies are categorized into five types: Taxonomic Relations (4,842 samples), Negation (1,630 samples), Set Based (642 samples), Gradable (526 samples), and Simple (415 samples).
@@ -153,6 +152,16 @@ Their expertise in the field ensured accurate and reliable annotations. The anno
 ## Additional Information
 
 ### Citation Information
+```
+@misc{raha2023neural,
+      title={Neural models for Factual Inconsistency Classification with Explanations}, 
+      author={Tathagata Raha and Mukund Choudhary and Abhinav Menon and Harshit Gupta and KV Aditya Srivatsa and Manish Gupta and Vasudeva Varma},
+      year={2023},
+      eprint={2306.08872},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
 
 ### Contact