Triple
T14853658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blow |
E349295
|
entity |
| Predicate | subject |
P450
|
FINISHED |
| Object | George Jung |
E129682
|
NE FINISHED |
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: George Jung | Statement: [Blow, subject, George Jung]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: George Jung Context triple: [Blow, subject, George Jung]
-
A.
George Jung
chosen
George Jung was an American drug trafficker and key figure in the U.S. cocaine trade of the 1970s and 1980s, whose life story inspired the film "Blow."
-
B.
Thomas Jung
Thomas Jung is a German politician who has served as the long-time mayor of the Bavarian city of Fürth.
-
C.
George Juergens
George Juergens is a central character on the teen drama series "The Secret Life of the American Teenager," known as the quirky, overprotective father navigating family turmoil and teenage pregnancy.
-
D.
Carl Werner
Carl Werner is a personal name shared by several notable individuals, including figures in fields such as art, science, and sports.
-
E.
Simon Sechter
Simon Sechter was a 19th-century Austrian music theorist, composer, and influential teacher of counterpoint, best known for mentoring composers such as Anton Bruckner.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded44318f0819080b6c599f2d3474f |
completed | April 14, 2026, 11:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6506ace48190819504b93f575660 |
completed | May 8, 2026, 10:34 p.m. |
Created at: April 10, 2026, 1:54 a.m.