Triple
T5112770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Life Story |
E115255
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
Michael Gunton
Michael Gunton is a British television producer best known for his work on major BBC natural history series such as Planet Earth II and Dynasties.
|
E493504
|
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: Michael Gunton | Statement: [Life Story, executiveProducer, Michael Gunton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Gunton Context triple: [Life Story, executiveProducer, Michael Gunton]
-
A.
Daniel Patterson
Daniel Patterson was the first husband of Mary Baker Eddy, the founder of Christian Science.
-
B.
Michael Kitchen
Michael Kitchen is a British actor best known for his versatile film and television roles, including the lead in the detective series "Foyle's War."
-
C.
David Huntley
David Huntley is an entrepreneur best known as a founder of the outdoor apparel and equipment company Mountain Hardwear.
-
D.
Jeffrey Hatcher
Jeffrey Hatcher is an American playwright and screenwriter known for his work in theater and film, including adaptations and period dramas.
-
E.
Alan Davidson
Alan Davidson is a U.S. technology policy expert and government official who has held senior roles shaping national internet, telecommunications, and digital policy.
- 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: Michael Gunton Triple: [Life Story, executiveProducer, Michael Gunton]
Generated description
Michael Gunton is a British television producer best known for his work on major BBC natural history series such as Planet Earth II and Dynasties.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Gunton Target entity description: Michael Gunton is a British television producer best known for his work on major BBC natural history series such as Planet Earth II and Dynasties.
-
A.
Daniel Patterson
Daniel Patterson was the first husband of Mary Baker Eddy, the founder of Christian Science.
-
B.
Michael Kitchen
Michael Kitchen is a British actor best known for his versatile film and television roles, including the lead in the detective series "Foyle's War."
-
C.
David Huntley
David Huntley is an entrepreneur best known as a founder of the outdoor apparel and equipment company Mountain Hardwear.
-
D.
Jeffrey Hatcher
Jeffrey Hatcher is an American playwright and screenwriter known for his work in theater and film, including adaptations and period dramas.
-
E.
Alan Davidson
Alan Davidson is a U.S. technology policy expert and government official who has held senior roles shaping national internet, telecommunications, and digital policy.
- 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_69bd4441d1648190a54a533895041987 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75cba1e88190af076657f846b975 |
completed | March 20, 2026, 4:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bebaaa394c8190bd93cdf57475a5b6 |
completed | March 21, 2026, 3:35 p.m. |
| NEDg | Description generation | batch_69bebb50aef48190b625278340a8c310 |
completed | March 21, 2026, 3:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bebc0b38e88190830eb74292e00e93 |
completed | March 21, 2026, 3:40 p.m. |
Created at: March 20, 2026, 1:41 p.m.