Triple
T9464087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A1 motorway (Germany) |
E228224
|
entity |
| Predicate | terminusNorth |
P3375
|
FINISHED |
| Object | Heiligenhafen |
E802355
|
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: Heiligenhafen | Statement: [A1 motorway (Germany), terminusNorth, Heiligenhafen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heiligenhafen Context triple: [A1 motorway (Germany), terminusNorth, Heiligenhafen]
-
A.
Heiligenhafen
chosen
Heiligenhafen is a coastal town in northern Germany on the Baltic Sea, known for its fishing harbor, beaches, and tourism.
-
B.
Ostuferhafen
Ostuferhafen is a major ferry and cargo terminal in Kiel, Germany, serving Baltic Sea routes and handling both passenger and freight traffic.
-
C.
Westhafen
Westhafen is a major inland port and freight hub in Berlin, serving as one of the city’s key logistics and transportation centers.
-
D.
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.
-
E.
Wallhausen
Wallhausen is a village in present-day Saxony-Anhalt, Germany, historically notable as the birthplace of Otto I, Holy Roman Emperor.
- 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_69ca846fee388190a6ec273fd644b88b |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7fcec2d88190b93b6e4d881c85c6 |
completed | April 1, 2026, 8:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d139ece5bc81908956e1f7ecbb1aa4 |
completed | April 4, 2026, 4:18 p.m. |
Created at: March 30, 2026, 7:53 p.m.