Triple
T1992587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Oldenburg |
E43283
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Oldenburg |
E73235
|
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: Oldenburg | Statement: [University of Oldenburg, locatedIn, Oldenburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oldenburg Context triple: [University of Oldenburg, locatedIn, Oldenburg]
-
A.
Oldenburg
chosen
Oldenburg is a historic university city in northwestern Germany known for its cultural heritage and role as a regional economic center.
-
B.
Bremerhaven
Bremerhaven is a major German port city on the North Sea, known for its maritime industry, shipbuilding, and role as a key hub for trade and logistics.
-
C.
Soest
Soest is a historic town in North Rhine-Westphalia, Germany, known for its well-preserved medieval architecture and former significance as a Hanseatic trading center.
-
D.
Lübeck
Lübeck is a historic Hanseatic city in northern Germany renowned for its medieval architecture and long-standing role as a key trading hub on the Baltic Sea.
-
E.
Lüneburg
Lüneburg is a historic Hanseatic town in northern Germany renowned for its medieval architecture and former wealth from salt mining.
- 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_69a88714cf2c819081644be450b8356e |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb86275c88190bed869e9d3cf7ed5 |
completed | March 7, 2026, 5:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae5179b3348190bfec5530baf4ca86 |
completed | March 9, 2026, 4:50 a.m. |
Created at: March 4, 2026, 7:37 p.m.