Triple
T6843911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hesse |
E157843
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Limburg an der Lahn |
E224973
|
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: Limburg an der Lahn | Statement: [Hesse, contains, Limburg an der Lahn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Limburg an der Lahn Context triple: [Hesse, contains, Limburg an der Lahn]
-
A.
Limburg an der Lahn
chosen
Limburg an der Lahn is a historic town in western Hesse, Germany, known for its well-preserved medieval old town and prominent hilltop cathedral overlooking the Lahn River.
-
B.
Limburg-Weilburg
Limburg-Weilburg is a rural district in the German state of Hesse, known for its historic town of Limburg an der Lahn and its location along the Lahn River.
-
C.
Limburg
Limburg is a historical region in the Low Countries that was once part of the Habsburg Netherlands and has since been divided mainly between present-day Belgium and the Netherlands.
-
D.
Limburg an der Vesdre
Limburg an der Vesdre is a historic town in eastern Belgium that once served as the capital of the medieval Duchy of Limburg.
-
E.
Wetzlar
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.
- 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_69c6882ed4c081909dc465a7cf8838be |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d6b7179481909e3482fef47b2719 |
completed | March 27, 2026, 7:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c72fbf06008190a8c342d3d7dec930 |
completed | March 28, 2026, 1:32 a.m. |
Created at: March 27, 2026, 2:19 p.m.