Triple
T12565997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamburg-Finkenwerder |
E295478
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Hamburg-Altenwerder |
E895870
|
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: Hamburg-Altenwerder | Statement: [Hamburg-Finkenwerder, locatedNear, Hamburg-Altenwerder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hamburg-Altenwerder Context triple: [Hamburg-Finkenwerder, locatedNear, Hamburg-Altenwerder]
-
A.
Altenwerder
chosen
Altenwerder is a district of Hamburg, Germany, known today primarily as the site of the highly automated Altenwerder container terminal in the Port of Hamburg.
-
B.
Hasselwerder
Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
-
C.
Hamburg-Finkenwerder
Hamburg-Finkenwerder is a district of Hamburg, Germany, known for its historic and ongoing role in shipbuilding and aviation industries along the River Elbe.
-
D.
Delmenhorst
Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
-
E.
Elmshorn
Elmshorn is a town in northern Germany’s Schleswig-Holstein state, known as an industrial and commuter hub northwest of Hamburg.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9549611c081909e611756f3cce7f0 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65eb71c548190826d243a354bd01c |
completed | May 2, 2026, 8:29 p.m. |
Created at: April 8, 2026, 11:49 p.m.