Triple
T1385617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Blake |
E29837
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Somerset |
E59760
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Somerset | Statement: [Robert Blake, birthPlace, Somerset]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Somerset Context triple: [Robert Blake, birthPlace, Somerset]
-
A.
Somerset
chosen
Somerset is a historic county in South West England known for its rural landscapes, coastal areas, and cities such as Bath and Wells.
-
B.
Somerset
Somerset is a coastal town in Bristol County, Massachusetts, situated along the Taunton River opposite the city of Fall River.
-
C.
Dorset
Dorset is a rural county on England’s south coast, known for its Jurassic Coast World Heritage Site, rolling countryside, and historic market towns.
-
D.
Herefordshire
Herefordshire is a predominantly rural county in the West Midlands of England, known for its agriculture, rolling countryside, and the cathedral city of Hereford.
-
E.
Shropshire
Shropshire is a largely rural county in the West Midlands of England, known for its historic market towns, rolling countryside, and parts of the Shropshire Hills Area of Outstanding Natural Beauty.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a498dc92f8819094a1108f8ac90f43 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c339f3d481909c04b14129899945 |
completed | March 1, 2026, 10:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae515ce1b0819089603a3e0f6b1933 |
completed | March 9, 2026, 4:49 a.m. |
Created at: March 1, 2026, 7:59 p.m.