Triple
T22432380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Health |
E554529
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
David Sinclair
David Sinclair is a prominent Australian biologist and Harvard Medical School professor known for his research on aging and longevity.
|
E290015
|
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: David Sinclair | Statement: [National Health, hasMember, David Sinclair]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Sinclair Context triple: [National Health, hasMember, David Sinclair]
-
A.
David Sinclair
David Sinclair was the son of American novelist and social reformer Upton Sinclair.
-
B.
David Sinclair (biologist)
David Sinclair is an Australian biologist and Harvard Medical School professor best known for his pioneering research on aging, sirtuins, and longevity therapeutics.
-
C.
Nigel de Grey
Nigel de Grey was a British cryptanalyst and intelligence officer renowned for his work in codebreaking at Room 40 during World War I.
-
D.
Geoffrey Hall
Geoffrey Hall is a cinematographer known for his work on films such as "Chopper," contributing distinctive visual style to Australian cinema.
-
E.
Douglas Ainslie
Douglas Ainslie is a mild-mannered, retired British man seeking a new start in India in the film "The Best Exotic Marigold Hotel," portrayed by Bill Nighy.
- 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: David Sinclair Triple: [National Health, hasMember, David Sinclair]
Generated description
David Sinclair is a prominent Australian biologist and Harvard Medical School professor known for his research on aging and longevity.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: David Sinclair Target entity description: David Sinclair is a prominent Australian biologist and Harvard Medical School professor known for his research on aging and longevity.
-
A.
David Sinclair
David Sinclair was the son of American novelist and social reformer Upton Sinclair.
-
B.
David Sinclair (biologist)
chosen
David Sinclair is an Australian biologist and Harvard Medical School professor best known for his pioneering research on aging, sirtuins, and longevity therapeutics.
-
C.
Nigel de Grey
Nigel de Grey was a British cryptanalyst and intelligence officer renowned for his work in codebreaking at Room 40 during World War I.
-
D.
Geoffrey Hall
Geoffrey Hall is a cinematographer known for his work on films such as "Chopper," contributing distinctive visual style to Australian cinema.
-
E.
Douglas Ainslie
Douglas Ainslie is a mild-mannered, retired British man seeking a new start in India in the film "The Best Exotic Marigold Hotel," portrayed by Bill Nighy.
- F. None of above.
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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15a3320448190ae3931062599116e |
completed | April 29, 2026, 1:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0af0f90f5881908f0011690cb0f1e4 |
completed | May 18, 2026, 10:59 a.m. |
| NEDg | Description generation | batch_6a0af268db2881908706641ad1e41f79 |
completed | May 18, 2026, 11:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b08e411048190a368214c57c35d5e |
completed | May 18, 2026, 12:41 p.m. |
Created at: April 16, 2026, 8:47 p.m.