Triple
T22257292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jake Bugg |
E550125
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Kennedy |
—
|
NE NERFINISHED |
How this triple was built (2 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: Kennedy | Statement: [Jake Bugg, familyName, Kennedy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kennedy Context triple: [Jake Bugg, familyName, Kennedy]
-
A.
Kennedy
chosen
Kennedy is a given name shared by various notable individuals across fields such as politics, music, and entertainment.
-
B.
Kennedy
Kennedy is a prominent Irish-American political and public-service family best known for producing U.S. President John F. Kennedy and numerous other influential politicians.
-
C.
Kennedy
Kennedy is a vast rural federal electoral division in Queensland, Australia, known for encompassing remote outback communities and mining towns.
-
D.
Kennedy
Kennedy is a scholar associated with the field of Classics, likely known for significant contributions to classical studies or literature.
-
E.
JFK
JFK is John F. Kennedy International Airport, a major international air travel hub serving New York City.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e42adb8819087714772ea606709 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f138c3cf64819087e270a1f50e629e |
completed | April 28, 2026, 10:46 p.m. |
Created at: April 16, 2026, 8:39 p.m.