Triple
T465591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angela Dorothea Kasner |
E8439
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Kasner |
E6716
|
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: Kasner | Statement: [Angela Dorothea Kasner, familyName, Kasner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kasner Context triple: [Angela Dorothea Kasner, familyName, Kasner]
-
A.
Kasner
chosen
Kasner is the birth surname of former German chancellor Angela Merkel, reflecting her family name before marriage.
-
B.
Bardeen
Bardeen is a surname most notably associated with John Bardeen, the American physicist who won the Nobel Prize in Physics twice for his work on the transistor and superconductivity.
-
C.
Blaustein
Blaustein is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm.
-
D.
Krafft
Krafft is a variant spelling of the surname Kraft, which is of German origin and borne by various notable individuals.
-
E.
Oppenheimer–Snyder model
The Oppenheimer–Snyder model is a pioneering theoretical description of gravitational collapse in general relativity, providing one of the first rigorous treatments of how a massive star can form a black hole.
- 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_69a2e7f3aeb48190a19453e3a043f486 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efd6ec708190b78c7f22deb3ca64 |
completed | Feb. 28, 2026, 1:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a452985bb48190890711440edcf598 |
completed | March 1, 2026, 2:52 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.