Triple
T5622894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John H. Schwarz |
E147649
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
John
John is the given name of the American theoretical physicist John H. Schwarz, a pioneering figure in the development of string theory.
|
E534864
|
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: John | Statement: [John H. Schwarz, givenName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [John H. Schwarz, givenName, John]
-
A.
John
John is the given name of John Adams, the prominent American minimalist and post-minimalist composer known for works like "Nixon in China" and "Short Ride in a Fast Machine."
-
B.
John
John is the given name of John Boyd-Carpenter, a prominent British Conservative politician who served in several senior government positions in the mid-20th century.
-
C.
John
John is the first name of John Dashwood, a character in Jane Austen's novel "Sense and Sensibility."
-
D.
John
John is the given first name of American character actor and comedian Rags Ragland.
-
E.
John
John is the given name of actor John Cho, a Korean American performer known for roles in the "Harold & Kumar" films and the "Star Trek" reboot series.
- 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: John Triple: [John H. Schwarz, givenName, John]
Generated description
John is the given name of the American theoretical physicist John H. Schwarz, a pioneering figure in the development of string theory.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Target entity description: John is the given name of the American theoretical physicist John H. Schwarz, a pioneering figure in the development of string theory.
-
A.
John
John is the given name of the influential American theoretical physicist John Archibald Wheeler, known for his work in quantum mechanics and general relativity.
-
B.
John
John is the given name of John Robert Schrieffer, the American physicist and Nobel laureate known for co-developing the BCS theory of superconductivity.
-
C.
John
John is the given name of John F. Clauser, an American physicist and Nobel laureate known for his pioneering experimental tests of quantum entanglement and Bell's inequalities.
-
D.
John
John is the given name of John Cockcroft, a pioneering British physicist and Nobel laureate known for his work on nuclear physics and particle acceleration.
-
E.
John
John is the given name of John Bardeen, the American physicist who uniquely won the Nobel Prize in Physics twice for his work on the transistor and superconductivity.
- 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_69c00906f2a88190a992c66b13d606d4 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c02214b4948190b71a9f59499092f6 |
completed | March 22, 2026, 5:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04ce1bce4819095559af19cf072f8 |
completed | March 22, 2026, 8:11 p.m. |
| NEDg | Description generation | batch_69c04e89b7c481908abae227d22cc814 |
completed | March 22, 2026, 8:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c04f41b158819097f9ef536215e248 |
completed | March 22, 2026, 8:21 p.m. |
Created at: March 22, 2026, 3:40 p.m.