Triple
T15435923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. John Becker |
E369761
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
John
John is the given name of the fictional character Dr. John Becker, a cynical Bronx doctor from the American television sitcom "Becker."
|
E1157441
|
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: [Dr. John Becker, givenName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [Dr. John Becker, givenName, John]
-
A.
John
John is the given name of John W. Mauchly, the American physicist and co-inventor of the ENIAC computer.
-
B.
John
John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
-
C.
John
John is the given name of John Albert William Spencer-Churchill, a British aristocrat and 10th Duke of Marlborough.
-
D.
John
John is the given first name of the 19th-century English theologian and social reformer Frederick Denison Maurice.
-
E.
John
John is the given name of Sir John Lennard-Jones, a pioneering British theoretical chemist known for his work on intermolecular forces and the Lennard-Jones potential.
- 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: [Dr. John Becker, givenName, John]
Generated description
John is the given name of the fictional character Dr. John Becker, a cynical Bronx doctor from the American television sitcom "Becker."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Target entity description: John is the given name of the fictional character Dr. John Becker, a cynical Bronx doctor from the American television sitcom "Becker."
-
A.
John
John is the given name of the fictional character Trapper John McIntyre from the M*A*S*H franchise.
-
B.
John
John is the given name of American character actor John McGiver, known for his distinctive, pompous persona in mid-20th-century film and television.
-
C.
John
John is the given name of John Bodkin Adams, a British physician notorious for being suspected of murdering numerous patients in the mid-20th century.
-
D.
John
John is the first name of the fictional character John Connor, the prophesied leader of the human resistance in the Terminator franchise.
-
E.
John
John is a fictional police detective and main character from the science fiction TV series "Almost Human."
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03edb3ec481908b26164d4470c9bc |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff21a3d1f481908f6795656514b2b4 |
completed | May 9, 2026, 11:59 a.m. |
| NEDg | Description generation | batch_69ff2299ac9481909ad213ff5bb01db3 |
completed | May 9, 2026, 12:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff2325e6a48190bee256ef8720ba8e |
completed | May 9, 2026, 12:05 p.m. |
Created at: April 10, 2026, 3:21 a.m.