Triple
T7625838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Günther |
E172627
|
entity |
| Predicate | transliteration |
P2508
|
FINISHED |
| Object | Guenther |
E172627
|
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: Guenther | Statement: [Günther, transliteration, Guenther]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guenther Context triple: [Günther, transliteration, Guenther]
-
A.
Eberl
Eberl is a German-language surname of Austrian and Bavarian origin borne by various notable individuals.
-
B.
Günther
Günther is the zoologist who first formally described the impressed tortoise species Manouria impressa.
-
C.
Günther
chosen
Günther is a German masculine given name traditionally associated with figures of Germanic origin and culture.
-
D.
Oberhauser
Oberhauser is a German-language surname borne by various notable individuals across fields such as sports, the arts, and public life.
-
E.
Garbitsch
Garbitsch is the sinister, Goebbels-like propaganda minister in Charlie Chaplin’s 1940 satirical film "The Great Dictator," played by actor Henry Daniell.
- 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_69c699517e348190bd3348b6889200f2 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fa8039148190a492a0a25bcc7c55 |
completed | March 27, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8a212d0888190a40cdf32ef53d993 |
completed | March 29, 2026, 3:52 a.m. |
Created at: March 27, 2026, 3:56 p.m.