Triple
T13673811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margaret Fell |
E327820
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Dalton-in-Furness |
E343223
|
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: Dalton-in-Furness | Statement: [Margaret Fell, placeOfBirth, Dalton-in-Furness]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dalton-in-Furness Context triple: [Margaret Fell, placeOfBirth, Dalton-in-Furness]
-
A.
Dalton-in-Furness
chosen
Dalton-in-Furness is a small historic market town in Cumbria, England, known as the former capital of the Furness area.
-
B.
Broughton-in-Furness
Broughton-in-Furness is a small historic market town in Cumbria, England, situated near the Lake District National Park.
-
C.
Workington
Workington is a coastal town and port on the west coast of England, historically known for its steel and coal industries and situated at the mouth of the River Derwent.
-
D.
Barrow-in-Furness
Barrow-in-Furness is a coastal industrial town in Cumbria, England, historically known for its shipbuilding and submarine construction.
-
E.
Furness
Furness is an English-origin surname borne by various notable figures, including scholars, architects, and public officials.
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc65aab348190a6611f5765f8392d |
completed | April 12, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78b145fa081908521c103201f3afe |
completed | May 3, 2026, 5:51 p.m. |
Created at: April 9, 2026, 9:53 p.m.