Triple
T1877337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taunus region |
E39173
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Weilburg |
E145657
|
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: Weilburg | Statement: [Taunus region, contains, Weilburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weilburg Context triple: [Taunus region, contains, Weilburg]
-
A.
Weilburg
chosen
Weilburg is a historic town in the German state of Hesse, known for its Renaissance castle and as the ancestral seat of the House of Nassau-Weilburg.
-
B.
Langenau
Langenau is a small town in the Alb-Donau district of Baden-Württemberg in southern Germany, known for its historic center and proximity to the Swabian Jura.
-
C.
Uerdingen
Uerdingen is a district of the German city of Krefeld, known historically for its chemical industry and location along the Rhine River.
-
D.
Badenweiler
Badenweiler is a spa town in southwestern Germany’s Black Forest region, known for its thermal baths and as the place where Russian writer Anton Chekhov died.
-
E.
Andernach
Andernach is a historic German town on the Rhine River in Rhineland-Palatinate, known for its medieval architecture and one of the world’s highest cold-water geysers.
- 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_69a8862f7074819096afe7fe65e179e9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0da543481908ab25806e6b80375 |
completed | March 7, 2026, 5 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af5cb503bc8190823a843bb58d85e1 |
completed | March 9, 2026, 11:50 p.m. |
Created at: March 4, 2026, 7:34 p.m.