Triple
T10473291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allenstein |
E246982
|
entity |
| Predicate | hasGermanName |
P1435
|
FINISHED |
| Object | Allenstein |
E246982
|
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: Allenstein | Statement: [Allenstein, hasGermanName, Allenstein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Allenstein Context triple: [Allenstein, hasGermanName, Allenstein]
-
A.
Allenstein
chosen
Allenstein, now known as Olsztyn, is a historic city in northern Poland that once served as an important administrative and cultural center of East Prussia.
-
B.
Ernst
Ernst is a masculine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
-
C.
Hanussen
Hanussen is a 1988 Austrian-German biographical drama film about the clairvoyant performer Erik Jan Hanussen, starring Klaus Maria Brandauer.
-
D.
Günther
Günther is the zoologist who first formally described the impressed tortoise species Manouria impressa.
-
E.
Günther
Günther is a German masculine given name traditionally associated with figures of Germanic origin and culture.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5094daac081908e0ba5e10c1bbb67 |
completed | April 7, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8a0140f4c81908ce95b28e09cb04b |
completed | April 10, 2026, 7 a.m. |
Created at: April 6, 2026, 12:20 p.m.