Triple
T1294539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murray Edwards College, Cambridge |
E27623
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Steve Edwards
Steve Edwards is the benefactor after whom Murray Edwards College at the University of Cambridge is named.
|
E203557
|
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: Steve Edwards | Statement: [Murray Edwards College, Cambridge, namedAfter, Steve Edwards]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steve Edwards Context triple: [Murray Edwards College, Cambridge, namedAfter, Steve Edwards]
-
A.
Jack Edwards
Jack Edwards is known primarily as the son of Austrian-American character actor Snitz Edwards.
-
B.
Eric Alan Edwards
Eric Alan Edwards is an American cinematographer known for his work on a range of feature films, including the comedy "Fist Fight."
-
C.
Timothy Edwards
Timothy Edwards was a colonial New England Congregational minister and scholar, best known as the father of theologian Jonathan Edwards.
-
D.
Michael Rogers
Michael Rogers is a relatively common personal name shared by multiple individuals across fields such as politics, sports, and the arts, rather than referring to one singular widely recognized figure.
-
E.
Ted Cheesman
Ted Cheesman was a film editor best known for his work on classic Hollywood productions, including the 1933 monster film "King Kong."
- 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: Steve Edwards Triple: [Murray Edwards College, Cambridge, namedAfter, Steve Edwards]
Generated description
Steve Edwards is the benefactor after whom Murray Edwards College at the University of Cambridge is named.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Steve Edwards Target entity description: Steve Edwards is the benefactor after whom Murray Edwards College at the University of Cambridge is named.
-
A.
Jack Edwards
Jack Edwards is known primarily as the son of Austrian-American character actor Snitz Edwards.
-
B.
Eric Alan Edwards
Eric Alan Edwards is an American cinematographer known for his work on a range of feature films, including the comedy "Fist Fight."
-
C.
Timothy Edwards
Timothy Edwards was a colonial New England Congregational minister and scholar, best known as the father of theologian Jonathan Edwards.
-
D.
Michael Rogers
Michael Rogers is a relatively common personal name shared by multiple individuals across fields such as politics, sports, and the arts, rather than referring to one singular widely recognized figure.
-
E.
Ted Cheesman
Ted Cheesman was a film editor best known for his work on classic Hollywood productions, including the 1933 monster film "King Kong."
- 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_69a496d6682881909ba658f1c1e0e2b0 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0f2eb608190a0ac47a73adae19b |
completed | March 1, 2026, 10:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adbf379d048190924ad8dfa9ac5e7a |
completed | March 8, 2026, 6:25 p.m. |
| NEDg | Description generation | batch_69adc07e9ebc819082566cc98025b4ae |
completed | March 8, 2026, 6:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adc12c894881909c9a82fc9e363a41 |
completed | March 8, 2026, 6:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.