Triple
T7028743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kurt Christoph von Königsmarck |
E163217
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Kurt |
E102649
|
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: Kurt | Statement: [Kurt Christoph von Königsmarck, givenName, Kurt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kurt Context triple: [Kurt Christoph von Königsmarck, givenName, Kurt]
-
A.
Kurt
chosen
Kurt is a given name most famously associated with the logician and mathematician Kurt Gödel.
-
B.
Kurt Weiss
Kurt Weiss is an individual notable enough to be recognized as a namesake of the surname Weiss, though specific widely known biographical details are not clearly established.
-
C.
Kurt Back
Kurt Back was a social psychologist known for his collaborative research in social behavior and group dynamics, including work with Leon Festinger.
-
D.
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.
-
E.
Karl
Karl is a ruthless, long-haired German terrorist and Hans Gruber’s vengeful right-hand man in the action film "Die Hard."
- 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_69c6885d691c81908cf7d31083113886 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e200ecdc819098ca07473dfb272a |
completed | March 27, 2026, 8:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7758c87908190bd1ddcfdccc171b5 |
completed | March 28, 2026, 6:30 a.m. |
Created at: March 27, 2026, 2:35 p.m.