Triple
T22965259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gänseliesel |
E571023
|
entity |
| Predicate | owner |
P347
|
FINISHED |
| Object | City of Göttingen |
—
|
NE NERFINISHED |
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: City of Göttingen | Statement: [Gänseliesel, owner, City of Göttingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Göttingen Context triple: [Gänseliesel, owner, City of Göttingen]
-
A.
Göttingen
chosen
Göttingen is a historic university city in Lower Saxony, Germany, renowned for its prestigious Georg-August University and contributions to science and mathematics.
-
B.
Heidberg
Heidberg is a small locality or district that forms part of the town of Rüthen in North Rhine-Westphalia, Germany.
-
C.
Erlangen
Erlangen is a city in northern Bavaria, Germany, known for its university, research institutions, and historical association with mathematician Emmy Noether.
-
D.
Gießen
Gießen is a mid-sized university city in central Germany known for its academic institutions and role as a regional administrative and cultural center.
-
E.
Duderstadt
Duderstadt is a historic small town in southern Lower Saxony, Germany, known for its well-preserved medieval timber-framed architecture and role as a regional center in the Eichsfeld area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245b2c6548190a0e4c7f2f7df2d48 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1822e542c8190a865f18e64fc0768 |
completed | April 29, 2026, 3:59 a.m. |
Created at: April 17, 2026, 3:47 p.m.