Triple
T20562297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ludwigsburg district |
E504872
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Marbach am Neckar |
—
|
NE NERFINISHED |
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: Marbach am Neckar | Statement: [Ludwigsburg district, hasTown, Marbach am Neckar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marbach am Neckar Context triple: [Ludwigsburg district, hasTown, Marbach am Neckar]
-
A.
Marbach am Neckar
chosen
Marbach am Neckar is a historic town in the German state of Baden-Württemberg, best known as the birthplace of the renowned poet and playwright Friedrich Schiller.
-
B.
Mühlacker
Mühlacker is a town in the state of Baden-Württemberg in southwestern Germany, known for its location in the Enz River valley and its historical radio transmitter.
-
C.
Marbach
Marbach is a district or locality within the town of Lauda-Königshofen in the state of Baden-Württemberg, Germany.
-
D.
Jagstzell
Jagstzell is a small municipality in the eastern Baden-Württemberg region of Germany, characterized by its rural setting and location within the Ostalb district.
-
E.
Vaihingen
Vaihingen is a district in the southwest of Stuttgart, Germany, known for its mix of residential areas, business parks, and proximity to major transport links.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4b6587c8190aee63dc7cff244ea |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a79f906c819081163de9649ccb17 |
completed | April 20, 2026, 10:24 p.m. |
Created at: April 16, 2026, 11:39 a.m.