leaderboard: add UltraBERT-150M clairic-extraction (zero-shot, #1)

README.md

@@ -48,7 +48,8 @@ their instructions, nothing else.
 | # | Model | Kind | Headline ↑ | Fields with a value ↑ | Hallucination ↓ | Miss ↓ | Computed ↑ | `p_null` AUROC ↑ |
 |---|---|---|---|---|---|---|---|---|
 | 1 | **[ScaleDown Extract](https://openrouter.ai/scaledown/extract)** | extraction API | **0.782** | 0.723 | 0.117 | 0.200 | 0.570 | – |
-| 2 | [Schematron V2 Small](https://openrouter.ai/inference-net/schematron-v2-small) | extraction LLM | **0.562** | 0.529 | 0.445 | 0.303 | 0.134 | – |
+| 2 | [UltraBERT-150M clairic-extraction](https://huggingface.co/tasksource/UltraBERT-150M-clairic-extraction) | span extractor, open 150M encoder | **0.616** | 0.548 | 0.141 | 0.297 | 0.013 | 0.815 |
+| 3 | [Schematron V2 Small](https://openrouter.ai/inference-net/schematron-v2-small) | extraction LLM | **0.562** | 0.529 | 0.445 | 0.303 | 0.134 | – |
 | – | Always null (answers nothing) | reference | **0.199** | 0.000 | 0.000 | 1.000 | 0.000 | – |
 | – | Regex rules | reference | **0.129** | 0.152 | 0.993 | 0.000 | 0.026 | 0.503 |
 
@@ -76,6 +77,14 @@ test-only families never appear in `train`, so they still test transfer.
   compute, and for fields that have a value the right answer is among their
   candidates only 49% of the time. That ceiling, not the classifier, is what holds them back. They are
   published as reproducible open baselines, not as competitive extractors.
+- **UltraBERT-150M clairic-extraction** (submitted by sileod, [discussion #1](https://huggingface.co/datasets/LocalLLaMA/typed-extraction/discussions/1))
+  is the first open-weight row. It tags answer spans per field with no LLM and
+  maps them to types in plain code, so it rarely computes values (0.013). Its
+  confidence is the raw span probability (ECE 0.42), but it ranks nulls well. We
+  re-scored the published predictions with the unmodified `score.py` and got the
+  same numbers. Its training data includes the SQuAD 2.0, DROP and CUAD train
+  splits; 23 test documents share text with it, and dropping them leaves the
+  headline at 0.616.
 - **Always null** answers nothing; it scores 0.199 because 31% of fields are
   absent. A model below it is doing more harm than good.
 - Remote models were called once, at temperature 0, with responses cached.