Triple
T21093839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karpf |
E519707
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Michael Karpf
Michael Karpf is a British physician and academic leader best known for his roles in hospital administration and medical education.
|
E1505312
|
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 Karpf | Statement: [Karpf, hasNotableBearer, Michael Karpf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Karpf Context triple: [Karpf, hasNotableBearer, Michael Karpf]
-
A.
Michael Vavitch
Michael Vavitch was a silent-era film actor known for his role in the 1924 drama "The Red Lily."
-
B.
Michael E. Bakich
Michael E. Bakich is an American astronomy writer, editor, and popularizer of observational astronomy, long associated with Astronomy magazine.
-
C.
Michael Wittenberg
Michael Wittenberg was an investment adviser best known as the late husband of Broadway star Bernadette Peters.
-
D.
Alan Schaefer
Alan Schaefer is the main special-forces commando protagonist, nicknamed "Dutch," portrayed by Arnold Schwarzenegger in the 1987 science fiction action film Predator.
-
E.
John Eisendrath
John Eisendrath is a television writer and producer best known for his work on series such as "The Blacklist" and "Alias."
- 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 Karpf Triple: [Karpf, hasNotableBearer, Michael Karpf]
Generated description
Michael Karpf is a British physician and academic leader best known for his roles in hospital administration and medical education.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Karpf Target entity description: Michael Karpf is a British physician and academic leader best known for his roles in hospital administration and medical education.
-
A.
Michael Vavitch
Michael Vavitch was a silent-era film actor known for his role in the 1924 drama "The Red Lily."
-
B.
Michael E. Bakich
Michael E. Bakich is an American astronomy writer, editor, and popularizer of observational astronomy, long associated with Astronomy magazine.
-
C.
Michael Wittenberg
Michael Wittenberg was an investment adviser best known as the late husband of Broadway star Bernadette Peters.
-
D.
Alan Schaefer
Alan Schaefer is the main special-forces commando protagonist, nicknamed "Dutch," portrayed by Arnold Schwarzenegger in the 1987 science fiction action film Predator.
-
E.
John Eisendrath
John Eisendrath is a television writer and producer best known for his work on series such as "The Blacklist" and "Alias."
- 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_69e0b507dd9081908fb8bfcbef4c8b46 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e709517a18819081ede1d38e2c4391 |
completed | April 21, 2026, 5:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a4bb108e08190ac6036fc6259cd8b |
completed | May 17, 2026, 11:13 p.m. |
| NEDg | Description generation | batch_6a0a4ccdd0a881908d32425b7cbb30c4 |
completed | May 17, 2026, 11:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a4de7d07c8190a0ccb1c229e7fc5d |
completed | May 17, 2026, 11:23 p.m. |
Created at: April 16, 2026, 2:51 p.m.