Triple
T2991657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lahn |
E80767
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Wetzlar |
E386707
|
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: Wetzlar | Statement: [Lahn, flowsThrough, Wetzlar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wetzlar Context triple: [Lahn, flowsThrough, Wetzlar]
-
A.
Wetzlar
chosen
Wetzlar is a historic German city in the state of Hesse, known for its medieval old town and its long tradition in optics and precision engineering.
-
B.
Wiesbaden
Wiesbaden is a historic spa city in western Germany known for its thermal springs, elegant architecture, and role as a regional administrative and cultural center.
-
C.
Hildesheim
Hildesheim is a historic city in northern Germany renowned for its medieval architecture and UNESCO-listed Romanesque churches.
-
D.
Darmstadt
Darmstadt is a city in the German state of Hesse known for its historical ties to the Grand Duchy of Hesse and its role as a center of science, technology, and Art Nouveau culture.
-
E.
Gießen
Gießen is a mid-sized university city in central Germany known for its academic institutions and role as a regional administrative and cultural center.
- 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_69ad8b16c3488190b47b6aa7a59a335b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99df69d08190a0e25efb0dc8d653 |
completed | March 8, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf7fbd0bc881908ba07edb75479b97 |
completed | March 22, 2026, 5:35 a.m. |
Created at: March 8, 2026, 2:59 p.m.