Triple
T1730971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord Lieutenant of Oxfordshire |
E37808
|
entity |
| Predicate | officeHoldersInclude |
P537
|
FINISHED |
| Object |
Tim Stevenson
Tim Stevenson is a British public servant who has served as the ceremonial representative of the monarch in Oxfordshire.
|
E230315
|
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: Tim Stevenson | Statement: [Lord Lieutenant of Oxfordshire, officeHoldersInclude, Tim Stevenson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tim Stevenson Context triple: [Lord Lieutenant of Oxfordshire, officeHoldersInclude, Tim Stevenson]
-
A.
Garth Stevenson
Garth Stevenson is a Canadian-born double bassist and composer known for his atmospheric, nature-inspired film scores and solo work.
-
B.
Don Stevens
Don Stevens is a notable individual recognized for achievements significant enough to be distinguished from others sharing the surname Stevens.
-
C.
Roger Stevens
Roger Stevens was a prominent British civil servant and diplomat who notably served as the first Vice-Chancellor of the University of Leeds.
-
D.
Ken Ralston
Ken Ralston is an acclaimed visual effects supervisor known for his groundbreaking work on major films such as the Star Wars and Back to the Future series.
-
E.
Mark Stevens
Mark Stevens was an American film and television actor best known for his roles in 1940s and 1950s dramas and film noir.
- 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: Tim Stevenson Triple: [Lord Lieutenant of Oxfordshire, officeHoldersInclude, Tim Stevenson]
Generated description
Tim Stevenson is a British public servant who has served as the ceremonial representative of the monarch in Oxfordshire.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tim Stevenson Target entity description: Tim Stevenson is a British public servant who has served as the ceremonial representative of the monarch in Oxfordshire.
-
A.
Garth Stevenson
Garth Stevenson is a Canadian-born double bassist and composer known for his atmospheric, nature-inspired film scores and solo work.
-
B.
Don Stevens
Don Stevens is a notable individual recognized for achievements significant enough to be distinguished from others sharing the surname Stevens.
-
C.
Roger Stevens
Roger Stevens was a prominent British civil servant and diplomat who notably served as the first Vice-Chancellor of the University of Leeds.
-
D.
Ken Ralston
Ken Ralston is an acclaimed visual effects supervisor known for his groundbreaking work on major films such as the Star Wars and Back to the Future series.
-
E.
Mark Stevens
Mark Stevens was an American film and television actor best known for his roles in 1940s and 1950s dramas and film noir.
- 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_69a8861cc6ac8190ac0b2e31ccf62851 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa63804cd48190aef5e0f231600e58 |
completed | March 6, 2026, 5:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae26ee4c088190a767d71f1a68a734 |
completed | March 9, 2026, 1:48 a.m. |
| NEDg | Description generation | batch_69ae277895488190ae4a2337cf2ae915 |
completed | March 9, 2026, 1:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae27e7113081909835657bfff3f9e8 |
completed | March 9, 2026, 1:52 a.m. |
Created at: March 4, 2026, 7:30 p.m.