Triple
T21236331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bundesautobahn 27 |
E523351
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | Bremerhaven |
—
|
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: Bremerhaven | Statement: [Bundesautobahn 27, passesNear, Bremerhaven]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bremerhaven Context triple: [Bundesautobahn 27, passesNear, Bremerhaven]
-
A.
Bremerhaven
chosen
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.
-
B.
Geesthacht
Geesthacht is a town in northern Germany known for its location on the Elbe River and its energy research and industrial facilities.
-
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.
Travemünde
Travemünde is a Baltic Sea resort town and seaside district of Lübeck in northern Germany, known for its beaches, harbor, and maritime tourism.
-
E.
Port of Bremen
The Port of Bremen is a major German river port complex on the Weser that serves as an important hub for maritime trade, logistics, and industry in northern Europe.
- 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_69e0b513b89c81908b27147e91368db2 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e735202c7481909c642ddaafb40671 |
completed | April 21, 2026, 8:28 a.m. |
Created at: April 16, 2026, 3:46 p.m.