Triple
T2218063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bloomsbury |
E48076
|
entity |
| Predicate | historicalCounty |
P1069
|
FINISHED |
| Object | Middlesex |
E14852
|
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: Middlesex | Statement: [Bloomsbury, historicalCounty, Middlesex]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Middlesex Context triple: [Bloomsbury, historicalCounty, Middlesex]
-
A.
Middlesex, England
chosen
Middlesex, England is a historic county in southeast England that once encompassed much of what is now Greater London.
-
B.
Middlesex Parish
Middlesex Parish was the former ecclesiastical parish name for the area that later became the town of Darien, Connecticut.
-
C.
Essex
Essex is a county in the east of England, known for its mix of rural landscapes, historic towns, and proximity to London.
-
D.
Uxbridge
Uxbridge is a suburban town in West London, England, known as a major commercial and administrative centre and the terminus of a branch of the London Underground.
-
E.
Uxbridge
Uxbridge is a township in Ontario, Canada, known for its rural landscapes, trail networks, and proximity to protected natural areas.
- 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_69a88aa1ee708190862c8c378c41e9eb |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc010bd4c8190ace293b37eac1de5 |
completed | March 7, 2026, 6:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae655b369c8190a5d12b87401534d7 |
completed | March 9, 2026, 6:14 a.m. |
Created at: March 4, 2026, 7:46 p.m.