Triple
T556058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edward Fox |
E11942
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object |
Robert Fox
Robert Fox is a British film and theatre producer known for his work on acclaimed stage and screen productions.
|
E101405
|
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 Fox | Statement: [Edward Fox, relative, Robert Fox]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robert Fox Context triple: [Edward Fox, relative, Robert Fox]
-
A.
John Gilroy
John Gilroy is a film editor known for his work on major Hollywood productions, including the science-fiction monster film "Pacific Rim."
-
B.
Rudulph Evans
Rudulph Evans was an American sculptor best known for creating the statue of Thomas Jefferson housed in the Jefferson Memorial in Washington, D.C.
-
C.
Luke Foxe
Luke Foxe was a 17th-century English explorer and navigator known for his Arctic voyages in search of the Northwest Passage.
-
D.
Robert Barker
Robert Barker was a 17th-century English royal printer best known for printing the first edition of the King James Bible.
-
E.
John L. Lumley
John L. Lumley was a prominent American fluid dynamicist known for his pioneering contributions to the understanding and modeling of turbulence.
- 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 Fox Triple: [Edward Fox, relative, Robert Fox]
Generated description
Robert Fox is a British film and theatre producer known for his work on acclaimed stage and screen productions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Robert Fox Target entity description: Robert Fox is a British film and theatre producer known for his work on acclaimed stage and screen productions.
-
A.
John Gilroy
John Gilroy is a film editor known for his work on major Hollywood productions, including the science-fiction monster film "Pacific Rim."
-
B.
Rudulph Evans
Rudulph Evans was an American sculptor best known for creating the statue of Thomas Jefferson housed in the Jefferson Memorial in Washington, D.C.
-
C.
Luke Foxe
Luke Foxe was a 17th-century English explorer and navigator known for his Arctic voyages in search of the Northwest Passage.
-
D.
Robert Barker
Robert Barker was a 17th-century English royal printer best known for printing the first edition of the King James Bible.
-
E.
John L. Lumley
John L. Lumley was a prominent American fluid dynamicist known for his pioneering contributions to the understanding and modeling of turbulence.
- 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4991ef9b0819092ec0407270373f4 |
completed | March 1, 2026, 7:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7a3a260888190b89e90c1da061733 |
completed | March 4, 2026, 3:14 a.m. |
| NEDg | Description generation | batch_69a7a5d4125481908fa8cbfefe39f7cd |
completed | March 4, 2026, 3:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7a6584acc81908a12da6f0c2faec5 |
completed | March 4, 2026, 3:26 a.m. |
Created at: March 1, 2026, 7:32 p.m.