Triple
T20960009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamburg S-Bahn |
E516213
|
entity |
| Predicate | hasTerminus |
P388
|
FINISHED |
| Object | Wedel |
E894696
|
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: Wedel | Statement: [Hamburg S-Bahn, hasTerminus, Wedel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wedel Context triple: [Hamburg S-Bahn, hasTerminus, Wedel]
-
A.
Wedel
chosen
Wedel is a town on the outskirts of Hamburg, Germany, known for being a suburban terminus of the city's S-Bahn network.
-
B.
Oudenburg
Oudenburg is a small historic town in the Belgian province of West Flanders, known for its Roman heritage and medieval abbey.
-
C.
Wolkenburg
Wolkenburg is a prominent hill in Germany’s Siebengebirge range, known for its volcanic origin and scenic views over the Rhine Valley.
-
D.
Ravensberg
Ravensberg was a historical county in northwestern Germany that became part of the expanding territorial holdings of Brandenburg-Prussia.
-
E.
Stolberg
Stolberg is a historic German town in the Harz region, known for its well-preserved medieval architecture and role in early Reformation-era history.
- 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_69e0b4fde6c48190af1398e7e734629e |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fb6e50988190a564d2aaf1a9bc54 |
completed | April 21, 2026, 4:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0927969140819089027995f14d86ee |
completed | May 17, 2026, 2:27 a.m. |
Created at: April 16, 2026, 1:30 p.m.