Triple
T3612175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tewkesbury |
E76512
|
entity |
| Predicate | twinnedWith |
P1072
|
FINISHED |
| Object | Miesbach |
E282753
|
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: Miesbach | Statement: [Tewkesbury, twinnedWith, Miesbach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miesbach Context triple: [Tewkesbury, twinnedWith, Miesbach]
-
A.
Miesbach
chosen
Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
-
B.
Biberach an der Riß
Biberach an der Riß is a historic town in the German state of Baden-Württemberg, known for its well-preserved medieval old town and traditional Swabian culture.
-
C.
Emsbach
Emsbach is a small river in Germany that flows through Hesse before joining the Lahn.
-
D.
Blaubeuren
Blaubeuren is a historic town in the Alb-Donau district of Baden-Württemberg, Germany, known for its medieval old town and the karst spring Blautopf.
-
E.
Schwandorf
Schwandorf is a town in the Upper Palatinate region of Bavaria, Germany, known as a local administrative and commercial center on the Naab River.
- 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_69ad85da0ba481908b3b48c69efe2b98 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc22e5b30819084184b730732c727 |
completed | March 8, 2026, 6:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4f01ef3e08190bb5ebfde40787ff2 |
completed | March 14, 2026, 5:20 a.m. |
Created at: March 8, 2026, 3:23 p.m.