Triple
T5580677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Günther Sabetzki |
E146631
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Günther |
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: Günther | Statement: [Günther Sabetzki, givenName, Günther]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Günther Context triple: [Günther Sabetzki, givenName, Günther]
-
A.
Günther
chosen
Günther is a German masculine given name traditionally associated with figures of Germanic origin and culture.
-
B.
Günther
Günther is the zoologist who first formally described the impressed tortoise species Manouria impressa.
-
C.
Othmar
Othmar is a masculine given name of Germanic origin, notably borne by the Swiss-American civil engineer Othmar Ammann.
-
D.
Hermann
Hermann Minkowski was a German mathematician best known for developing the geometric formulation of special relativity using four-dimensional spacetime.
-
E.
Hermann
Hermann is a German surname borne by various notable individuals across fields such as philosophy, science, and the arts.
- 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_69c0090287a08190b4098411effe970c |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0206d62548190b8a3c6efc1825661 |
completed | March 22, 2026, 5:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c097c480cc8190a42001a4c0b065a2 |
completed | March 23, 2026, 1:30 a.m. |
Created at: March 22, 2026, 3:37 p.m.