Update README.md

README.md

@@ -43,7 +43,9 @@ Each example includes: the NLQ, database identifier, a canonical dataset id, the
   - `id` *(int)* — Local entity id (unique within the example)
   - `type` *("table"|"column"|"value")*
   - `value` *(str)* — Surface form from the DB schema or literal value
-- `entity_to_token` *(List[Object])* — Each item has: `entity_id` *(int)*, `token_idxs` *(List[int])*
+- `entity_to_token` *(List[Object])* — Reverse index:
+  - `entity_id` *(int)* — Refers to an `entities[*].id`
+  - `token_idxs` *(List[int])* — Token indices composing that entity in `tokens`
 - `dber_tags` *(List[str])* — **CoNLL-style IOB2** tags over `tokens`
 
 ---
@@ -70,7 +72,7 @@ Each example includes: the NLQ, database identifier, a canonical dataset id, the
 
 ---
 
-## Example instances
+## Example
 ```json
 {
   "question_id": 13692,
@@ -80,28 +82,37 @@ Each example includes: the NLQ, database identifier, a canonical dataset id, the
   "SQL": "SELECT T1.first, T1.middle, T1.last FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.year BETWEEN 1980 AND 2000 AND T1.sex = 'Male' AND T2.`Submitted via` = 'Referral'",
   "tokens": ["Among","the","clients","born","between","1980","and","2000",",","list","the","name","of","male","clients","who","complained","through","referral","."],
   "entities": [
-    {"id":0,"type":"column","value":"first"},
-    {"id":1,"type":"column","value":"middle"},
-    {"id":2,"type":"column","value":"last"},
-    {"id":3,"type":"table","value":"client"},
-    {"id":4,"type":"table","value":"events"},
-    {"id":5,"type":"column","value":"client_id"},
-    {"id":6,"type":"column","value":"year"},
-    {"id":7,"type":"value","value":"1980"},
-    {"id":8,"type":"value","value":"2000"},
-    {"id":9,"type":"column","value":"sex"}
-    {"id":10,"type":"value","value":"Male"},
-    {"id":11,"type":"column","value":"Submitted via"},
-    {"id":12,"type":"value","value":"Referral"},
+    {"id": 0, "type": "column", "value": "first"},
+    {"id": 1, "type": "column", "value": "middle"},
+    {"id": 2, "type": "column", "value": "last"},
+    {"id": 3, "type": "table", "value": "client"},
+    {"id": 4, "type": "table", "value": "events"},
+    {"id": 5, "type": "column", "value": "client_id"},
+    {"id": 6, "type": "column", "value": "year"},
+    {"id": 7, "type": "value", "value": "1980"},
+    {"id": 8, "type": "value", "value": "2000"},
+    {"id": 9, "type": "column", "value": "sex"},
+    {"id": 10, "type": "value", "value": "Male"},
+    {"id": 11, "type": "column", "value": "Submitted via"},
+    {"id": 12, "type": "value", "value": "Referral"}
+  ]
+  "entity_to_token": [
+    ...,
+    {"entity_id":3,"token_idxs":[2]},
+    {"entity_id":5,"token_idxs":[14]},
+    {"entity_id":7,"token_idxs":[5]},
+    {"entity_id":8,"token_idxs":[7]},
+    {"entity_id":10,"token_idxs":[13]},
+    {"entity_id":12,"token_idxs":[18]},
+    ...
   ],
-  "entity_to_token": {"3":[2],"7":[5],"8":[7],"10":[13],"5":[14],"12":[18]},
   "dber_tags": ["O","O","B-TABLE","O","O","B-VALUE","O","B-VALUE","O","O","O","O","O","B-VALUE","B-COLUMN","O","O","O","B-VALUE","O"]
 }
 ```
 
 ---
 
-## How to load
+## Usage
 
 ### Load JSONL files
 ```python
@@ -125,7 +136,7 @@ ds = load_dataset("Voice49/dber")
 
 ---
 
-## Annotation (human + synthetic)
+## Annotation
 - **Human**: collaborative web UI with schema and SQL visible during labeling.
 - **Synthetic**: for each NLQ–SQL pair, generate candidate spans with Jaccard/Levenshtein, then solve a **non-overlapping ILP** to select spans maximizing similarity. Hyperparameters are validated on human data.
 
@@ -137,9 +148,6 @@ ds = load_dataset("Voice49/dber")
 
 <!-- ---
 
-## Licensing
-- **License:** `other` (see the repository `LICENSE` for terms). Research use only unless otherwise permitted.
-
 ---
 
 ## Citation
@@ -157,5 +165,6 @@ If you use **DB-ER**, please cite:
 
 ---
 
-## Release notes
+## Release notes  
+- **v1.1 (2025-08-26):** HF Data Viewer compatibility update
 - **v1.0:** Initial public release