Triple
T334396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A44 road |
E6692
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Worcester |
E112481
|
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: Worcester | Statement: [A44 road, passesThrough, Worcester]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Worcester Context triple: [A44 road, passesThrough, Worcester]
-
A.
Worcester, Massachusetts
Worcester, Massachusetts is a major city in central Massachusetts known as a historic industrial and educational hub often called the "Heart of the Commonwealth."
-
B.
Ipswich
Ipswich is a historic town and port in Suffolk, England, known as one of the country’s oldest continuously inhabited settlements.
-
C.
Worcester, England
chosen
Worcester, England is a historic cathedral city in the West Midlands of England, known for its medieval architecture, role in the English Civil War, and as the namesake of Worcester, Massachusetts.
-
D.
Fitchburg
Fitchburg is a small city in north-central Massachusetts known for its industrial history, hilly terrain, and role as a regional rail hub.
-
E.
Northampton
Northampton is a historic market town and the county town of Northamptonshire in the East Midlands of England.
- 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_69a2e79434908190a9d5afe415153ad9 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eac641708190b85fa21368e5de8e |
completed | Feb. 28, 2026, 1:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac2a016f68819098d8fa3ec0f6adfa |
completed | March 7, 2026, 1:37 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.