Triple
T1336375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Spodden |
E28758
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Whitworth |
E124570
|
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: Whitworth | Statement: [River Spodden, flowsThrough, Whitworth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Whitworth Context triple: [River Spodden, flowsThrough, Whitworth]
-
A.
Whitworth
chosen
Whitworth is a small town in Lancashire, England, situated in the Rossendale Valley between Rochdale and Bacup.
-
B.
Denison
Denison is a city in north Texas known for its railroad heritage and as the birthplace of U.S. President Dwight D. Eisenhower.
-
C.
Woodward
Woodward is a surname most prominently associated with American investigative journalist Bob Woodward, known for his reporting on the Watergate scandal.
-
D.
Bessemer
Bessemer is an industrial city in Jefferson County, Alabama, historically known for its steelmaking and manufacturing.
-
E.
Bessemer
Bessemer is a surname most notably associated with Sir Henry Bessemer, the English inventor who revolutionized steel production in the 19th century.
- 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1ecb5208190a9eadda113c91e66 |
completed | March 1, 2026, 10:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acc62b9bd081909dbe22cbea03f21f |
completed | March 8, 2026, 12:43 a.m. |
Created at: March 1, 2026, 7:55 p.m.