Triple
T16763339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wesel station |
E407400
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Wesel |
E89464
|
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: Wesel | Statement: [Wesel station, locatedIn, Wesel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wesel Context triple: [Wesel station, locatedIn, Wesel]
-
A.
Wesel
chosen
Wesel is a historic city in western Germany, located on the Rhine River in the state of North Rhine-Westphalia.
-
B.
Viersen
Viersen is a town in western Germany’s North Rhine-Westphalia, known for its proximity to Mönchengladbach and its role as a local administrative and cultural center.
-
C.
Erftstadt
Erftstadt is a town in the Rhein-Erft district of North Rhine-Westphalia, Germany, located southwest of Cologne and known for its mix of historic villages and suburban residential areas.
-
D.
Merzig
Merzig is a town in the Saarland region of western Germany, near the borders with France and Luxembourg.
-
E.
City of Wesel
The City of Wesel is a historic German town on the Lower Rhine that became an important Reformation and trading center in the early modern period.
- 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_69d8839174188190909f190097207065 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3abee862c819086d9bf01e623a8ce |
completed | April 18, 2026, 4:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d45013048190a8073f34820ca85a |
completed | May 10, 2026, 6:54 p.m. |
Created at: April 10, 2026, 5:21 a.m.