Triple
T11301005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Clinton (musician) |
E267585
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
George
George is the given name of George Clinton, the influential American funk musician and bandleader behind Parliament-Funkadelic.
|
E919596
|
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: George | Statement: [George Clinton (musician), givenName, George]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: George Context triple: [George Clinton (musician), givenName, George]
-
A.
George
George is the heroic protagonist of the fantasy film "The Magic Sword," known for embarking on a perilous quest to rescue a princess from an evil sorcerer.
-
B.
George
George is a common English surname of likely Greek and Latin origin, associated with numerous notable historical and contemporary figures.
-
C.
George
George is the given name of George Murray, 6th Duke of Atholl, a Scottish peer and nobleman of the 19th century.
-
D.
George
George is the given name of George de Hevesy, the Hungarian radiochemist and Nobel laureate known for pioneering the use of radioactive tracers in studying chemical processes.
-
E.
George
George is a supporting character in the romantic comedy film "27 Dresses," serving as a colleague and love interest within the story’s central wedding-planning world.
- 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: George Triple: [George Clinton (musician), givenName, George]
Generated description
George is the given name of George Clinton, the influential American funk musician and bandleader behind Parliament-Funkadelic.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: George Target entity description: George is the given name of George Clinton, the influential American funk musician and bandleader behind Parliament-Funkadelic.
-
A.
George
George is the given first name of Geordie Hormel, an American musician, composer, and heir to the Hormel meatpacking fortune.
-
B.
George
George is a male given name commonly used in English-speaking countries and borne by numerous historical figures, including kings, presidents, and cultural icons.
-
C.
George
George is the first name of George Strait, the American country music singer known as the "King of Country."
-
D.
George
George is the given name of George C. Pimentel, a prominent American chemist known for his work in chemical lasers and molecular spectroscopy.
-
E.
George
George is the given name of Sir George Grey, a prominent 19th-century British colonial governor and statesman.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9a4aad4819097384e1b591be2e3 |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e542df01fc81908539407e20543002 |
completed | April 19, 2026, 9:02 p.m. |
| NEDg | Description generation | batch_69e545ad9840819096cb11f1d427ea38 |
completed | April 19, 2026, 9:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e548c50aac81909f94ac2f35a29f41 |
completed | April 19, 2026, 9:27 p.m. |
Created at: April 8, 2026, 9:32 p.m.