Triple
T2261900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Hamburg |
E50057
|
entity |
| Predicate | localName |
P657
|
FINISHED |
| Object | Hamburger Hafen |
E50057
|
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: Hamburger Hafen | Statement: [Port of Hamburg, localName, Hamburger Hafen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hamburger Hafen Context triple: [Port of Hamburg, localName, Hamburger Hafen]
-
A.
Gstadt harbor
Gstadt harbor is a lakeside port and departure point on the shores of Lake Chiemsee in Bavaria, Germany, serving as a gateway to the lake’s islands and surrounding attractions.
-
B.
Port of Flensburg
The Port of Flensburg is a small commercial and ferry harbor on the Flensburg Fjord near the German-Danish border, serving regional maritime trade and tourism.
-
C.
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.
-
D.
Port of Hamburg
chosen
The Port of Hamburg is Germany’s largest seaport and a major European logistics hub, known as the country’s “Gateway to the World.”
-
E.
Port of Kiel
The Port of Kiel is a major Baltic Sea seaport and ferry hub known for passenger and cargo traffic, particularly on routes between Germany and Scandinavia and the Baltic states.
- 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_69a88b01e0048190ba96431b5f990ba9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc18aa9d48190893ca32558730e9c |
completed | March 7, 2026, 6:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71cdacb48190bc11e9e0e6b61ba0 |
completed | March 9, 2026, 7:07 a.m. |
Created at: March 4, 2026, 7:48 p.m.