Triple
T7274876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vannes |
E162998
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Cuxhaven |
E238867
|
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: Cuxhaven | Statement: [Vannes, twinTown, Cuxhaven]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cuxhaven Context triple: [Vannes, twinTown, Cuxhaven]
-
A.
Cuxhaven
chosen
Cuxhaven is a German port city on the North Sea coast that historically served as an important naval and maritime hub.
-
B.
Wilhelmshaven
Wilhelmshaven is a coastal city in northwestern Germany known for its major naval base and port on the North Sea.
-
C.
Itzehoe
Itzehoe is a historic town in northern Germany known for its medieval origins and role as a regional center in the state of Schleswig-Holstein.
-
D.
Aurich
Aurich is a historic town in northwestern Germany that serves as one of the principal urban centers of the East Frisia region in Lower Saxony.
-
E.
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.
- 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_69c6885c5964819085b209701769877f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb0fd8788190aa21d4b2ad773926 |
completed | March 27, 2026, 8:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7db2c76fc81909632c7ee4e54f81c |
completed | March 28, 2026, 1:44 p.m. |
Created at: March 27, 2026, 2:58 p.m.