Triple
T349957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamburg |
E7419
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | Port of Hamburg |
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: Port of Hamburg | Statement: [Hamburg, knownFor, Port of Hamburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Port of Hamburg Context triple: [Hamburg, knownFor, Port of Hamburg]
-
A.
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.”
-
B.
Hamburg
Hamburg is Germany’s second-largest city and a major northern European port and cultural center on the River Elbe.
-
C.
Port of Antwerp
The Port of Antwerp is one of Europe’s largest and busiest seaports, serving as a key international hub for maritime trade, logistics, and industry in Belgium.
-
D.
Port of Amsterdam
The Port of Amsterdam is one of Europe’s largest seaports and a major hub for maritime trade, logistics, and industry in the Netherlands.
-
E.
Duisburg
Duisburg is a major industrial and port city in western Germany’s Ruhr region, known for its steel production and one of the world’s largest inland harbors.
- 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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eb1f028c819098fa6480b4ca5cf0 |
completed | Feb. 28, 2026, 1:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a40ad03f5c819085d2c7686f4d2809 |
completed | March 1, 2026, 9:45 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.