Triple
T17935146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warden of Wadham College |
E448442
|
entity |
| Predicate | officeHeldBy |
P537
|
FINISHED |
| Object |
Robert Beddard
Robert Beddard is a British historian and academic known for his scholarship on early modern England and his leadership role at the University of Oxford.
|
E1327229
|
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: Robert Beddard | Statement: [Warden of Wadham College, officeHeldBy, Robert Beddard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robert Beddard Context triple: [Warden of Wadham College, officeHeldBy, Robert Beddard]
-
A.
Stephen Dyer
Stephen Dyer is a screenwriter best known for co-writing the 2011 romantic comedy film "Hysteria."
-
B.
Rob Humphreys
Rob Humphreys is a musician best known for his past role as a member of the California-based rock band Animal Liberation Orchestra (ALO).
-
C.
Geoffrey Beevers
Geoffrey Beevers is a British actor best known to Doctor Who fans for his chilling portrayal of the villainous Time Lord known as the Master.
-
D.
Denis Bedlow
Denis Bedlow is a film editor known for his work on the 2015 romantic drama film "Love," directed by Gaspar Noé.
-
E.
Roger Lupton
Roger Lupton was a 16th-century English clergyman and educational benefactor best known for his role in establishing Sedbergh School.
- 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: Robert Beddard Triple: [Warden of Wadham College, officeHeldBy, Robert Beddard]
Generated description
Robert Beddard is a British historian and academic known for his scholarship on early modern England and his leadership role at the University of Oxford.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Robert Beddard Target entity description: Robert Beddard is a British historian and academic known for his scholarship on early modern England and his leadership role at the University of Oxford.
-
A.
Stephen Dyer
Stephen Dyer is a screenwriter best known for co-writing the 2011 romantic comedy film "Hysteria."
-
B.
Rob Humphreys
Rob Humphreys is a musician best known for his past role as a member of the California-based rock band Animal Liberation Orchestra (ALO).
-
C.
Geoffrey Beevers
Geoffrey Beevers is a British actor best known to Doctor Who fans for his chilling portrayal of the villainous Time Lord known as the Master.
-
D.
Denis Bedlow
Denis Bedlow is a film editor known for his work on the 2015 romantic drama film "Love," directed by Gaspar Noé.
-
E.
Roger Lupton
Roger Lupton was a 16th-century English clergyman and educational benefactor best known for his role in establishing Sedbergh School.
- 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_69d8b9f79d14819095540856928f0e25 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a55536e0819083dcfc4be71d447a |
completed | April 19, 2026, 9:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a047125683081908a18067ff3fd7956 |
completed | May 13, 2026, 12:40 p.m. |
| NEDg | Description generation | batch_6a04730c241c8190800aa4c99dfa5c08 |
completed | May 13, 2026, 12:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0473c5c03c8190956a5d640cfd579d |
completed | May 13, 2026, 12:51 p.m. |
Created at: April 10, 2026, 10:21 a.m.