Triple
T17975062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karl |
E449448
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Karl |
—
|
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: Karl | Statement: [Karl, fullName, Karl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karl Context triple: [Karl, fullName, Karl]
-
A.
Karl
Karl is the given first name of Charles Proteus Steinmetz, the renowned German-American mathematician and electrical engineer who revolutionized the understanding of alternating current systems.
-
B.
Karl
Karl is a ruthless, long-haired German terrorist and Hans Gruber’s vengeful right-hand man in the action film "Die Hard."
-
C.
Karl
Karl Schwarzschild was a German physicist and astronomer best known for providing the first exact solution to Einstein’s field equations, leading to the concept of the Schwarzschild black hole.
-
D.
Karl
Karl is the given name of Karl Ritter von Halt, a notable German sports official and International Olympic Committee member in the early to mid-20th century.
-
E.
Karl
Karl is the given name of Karl Liebknecht, the German socialist politician and co-founder of the Communist Party of Germany.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d8b9f9927c8190a006110c8b996e61 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b1fee86c8190a9a220b008e78e10 |
completed | April 19, 2026, 10:44 a.m. |
Created at: April 10, 2026, 10:22 a.m.