Triple
T10749247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Horace Howard Furness |
E253530
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Furness
Furness is an English-origin surname borne by various notable figures, including scholars, architects, and public officials.
|
E884377
|
NE FINISHED |
How this triple was built (4 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: Furness | Statement: [Horace Howard Furness, familyName, Furness]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Furness Context triple: [Horace Howard Furness, familyName, Furness]
-
A.
Furness Vale
Furness Vale is a small village in Derbyshire, England, situated in the High Peak area of the Peak District.
-
B.
Barrow and Furness
Barrow and Furness is a UK parliamentary constituency in Cumbria that includes the industrial town of Barrow-in-Furness and surrounding areas.
-
C.
High Furness
High Furness is the upland, largely rural and scenic northern part of the Furness Peninsula in Cumbria, England, known for its fells, forests, and proximity to the Lake District.
-
D.
Torpenhow
Torpenhow is a small village in the Allerdale district of Cumbria, England, known for its historic church and distinctive place-name.
-
E.
Durnford
Durnford is an English surname most notably associated with British military officer Colonel Anthony Durnford, who served in the 19th century.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Furness Triple: [Horace Howard Furness, familyName, Furness]
Generated description
Furness is an English-origin surname borne by various notable figures, including scholars, architects, and public officials.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Furness Target entity description: Furness is an English-origin surname borne by various notable figures, including scholars, architects, and public officials.
-
A.
Furness Vale
Furness Vale is a small village in Derbyshire, England, situated in the High Peak area of the Peak District.
-
B.
Barrow and Furness
Barrow and Furness is a UK parliamentary constituency in Cumbria that includes the industrial town of Barrow-in-Furness and surrounding areas.
-
C.
High Furness
High Furness is the upland, largely rural and scenic northern part of the Furness Peninsula in Cumbria, England, known for its fells, forests, and proximity to the Lake District.
-
D.
Torpenhow
Torpenhow is a small village in the Allerdale district of Cumbria, England, known for its historic church and distinctive place-name.
-
E.
Durnford
Durnford is an English surname most notably associated with British military officer Colonel Anthony Durnford, who served in the 19th century.
- F. None of above. chosen
Provenance (5 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d71dbecd58819081e859ebf72f656c |
completed | April 9, 2026, 3:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de231af7388190b73347a3ffc1077a |
completed | April 14, 2026, 11:20 a.m. |
| NEDg | Description generation | batch_69de27fb843c81908c0d0a5fb231543f |
completed | April 14, 2026, 11:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69de2dff4a048190823c8b5f1f7ea548 |
completed | April 14, 2026, 12:07 p.m. |
Created at: April 8, 2026, 9:15 p.m.