Triple
T21158852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noble |
E521381
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Andrew Noble (physicist)
Andrew Noble is a physicist known for his contributions to theoretical and mathematical physics.
|
E1468569
|
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: Andrew Noble (physicist) | Statement: [Noble, hasNotableBearer, Andrew Noble (physicist)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew Noble (physicist) Context triple: [Noble, hasNotableBearer, Andrew Noble (physicist)]
-
A.
David Noble
David Noble is an Australian park ranger and botanist best known for discovering the rare and ancient Wollemi pine (Wollemia nobilis) in 1994.
-
B.
Robert Leighton
Robert Leighton is a film editor known for his work on notable movies including the baseball romantic comedy "Bull Durham."
-
C.
Geoffrey Smith
Geoffrey Smith is an Australian Anglican archbishop who serves as the national leader (Primate) of the Anglican Church of Australia.
-
D.
Nicholas Barber
Nicholas Barber is a British journalist and film critic known for his work with outlets such as the BBC and The Independent.
-
E.
John Malcolm
John Malcolm is the emotionally reserved army major whose strained relationship with his ex-wife forms one of the central storylines in the 1958 British drama film "Separate Tables."
- 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: Andrew Noble (physicist) Triple: [Noble, hasNotableBearer, Andrew Noble (physicist)]
Generated description
Andrew Noble is a physicist known for his contributions to theoretical and mathematical physics.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Andrew Noble (physicist) Target entity description: Andrew Noble is a physicist known for his contributions to theoretical and mathematical physics.
-
A.
David Noble
David Noble is an Australian park ranger and botanist best known for discovering the rare and ancient Wollemi pine (Wollemia nobilis) in 1994.
-
B.
Robert Leighton
Robert Leighton is a film editor known for his work on notable movies including the baseball romantic comedy "Bull Durham."
-
C.
Geoffrey Smith
Geoffrey Smith is an Australian Anglican archbishop who serves as the national leader (Primate) of the Anglican Church of Australia.
-
D.
Nicholas Barber
Nicholas Barber is a British journalist and film critic known for his work with outlets such as the BBC and The Independent.
-
E.
John Malcolm
John Malcolm is the emotionally reserved army major whose strained relationship with his ex-wife forms one of the central storylines in the 1958 British drama film "Separate Tables."
- 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_69e0b50d1ea481909c07e63c3ead9316 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7252e9ef481908f4904c535f3da8b |
completed | April 21, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a096dce16e08190bbf4d690b642822e |
completed | May 17, 2026, 7:27 a.m. |
| NEDg | Description generation | batch_6a096e90901081909f96dcf0a7acb6cd |
completed | May 17, 2026, 7:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a096f0ce3bc8190a5a82d718a898e13 |
completed | May 17, 2026, 7:32 a.m. |
Created at: April 16, 2026, 2:59 p.m.