Triple
T14070126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stolberg Castle |
E338583
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Stolberg |
E272832
|
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: Stolberg | Statement: [Stolberg Castle, locatedIn, Stolberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stolberg Context triple: [Stolberg Castle, locatedIn, Stolberg]
-
A.
Stolberg
chosen
Stolberg is a historic German town in the Harz region, known for its well-preserved medieval architecture and role in early Reformation-era history.
-
B.
Abensberg
Abensberg is a historic town in Bavaria, Germany, known for its medieval architecture and its role as a Napoleonic-era battlefield.
-
C.
Langenburg
Langenburg is a small historic town in the German state of Baden-Württemberg, known for its hilltop castle and association with various noble families.
-
D.
Badenburg
Badenburg is an ornate pavilion within Munich’s Nymphenburg Palace park, known for its richly decorated interiors and historical bathing hall.
-
E.
Katharinenfeld
Katharinenfeld was the historical German settler colony that later became the town of Bolnisi in southern Georgia.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de568d0404819087e0fe37c72162cb |
completed | April 14, 2026, 3 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcb66cfe2c8190af8354316d4f4df9 |
completed | May 7, 2026, 3:57 p.m. |
Created at: April 9, 2026, 10:21 p.m.