Triple
T16886737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teesside |
E421558
|
entity |
| Predicate | majorTown |
P316
|
FINISHED |
| Object | Middlesbrough |
E219312
|
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: Middlesbrough | Statement: [Teesside, majorTown, Middlesbrough]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Middlesbrough Context triple: [Teesside, majorTown, Middlesbrough]
-
A.
Middlesbrough
chosen
Middlesbrough is a large industrial town and port in North Yorkshire, England, known historically for its steelmaking and chemical industries on the River Tees.
-
B.
Barnsley
Barnsley is a large market town and former industrial centre in South Yorkshire, England, historically known for coal mining and glassmaking.
-
C.
Huddersfield
Huddersfield is a large market town in West Yorkshire, England, known for its Victorian architecture, university, and role in the Industrial Revolution.
-
D.
Sunderland
Sunderland is a coastal city in Tyne and Wear, North East England, historically known for its shipbuilding and coal-mining industries and now a center for services, education, and automotive manufacturing.
-
E.
Sunderland
Sunderland is a small rural community in the township of Brock in Durham Region, Ontario, Canada.
- 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_69d889d470fc8190b4aec199636c0c56 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3bbc126e881909dae8133ad34acc9 |
completed | April 18, 2026, 5:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c7a61c608190909a462e9e77220b |
completed | May 10, 2026, 6 p.m. |
Created at: April 10, 2026, 5:29 a.m.