Triple
T15183671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stadt des KdF-Wagens bei Fallersleben |
E362811
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Fallersleben |
E290470
|
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: Fallersleben | Statement: [Stadt des KdF-Wagens bei Fallersleben, near, Fallersleben]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fallersleben Context triple: [Stadt des KdF-Wagens bei Fallersleben, near, Fallersleben]
-
A.
Fallersleben
chosen
Fallersleben is a district of Wolfsburg in Lower Saxony, Germany, historically known as the birthplace of poet August Heinrich Hoffmann von Fallersleben.
-
B.
Roßleben
Roßleben is a small town in the Unstrut valley of central Germany, known for its historic monastery and long-standing educational traditions.
-
C.
Faulbach
Faulbach is a district (Ortsteil) of the town of Hadamar in the Limburg-Weilburg district of Hesse, Germany.
-
D.
Landersdorf
Landersdorf is a locality within the city of Krems an der Donau in Lower Austria, known as part of its surrounding wine-growing and rural area.
-
E.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
- 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_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006674c088190ba635a78c30f5637 |
completed | April 15, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fec893f1e08190a192b7b9b80484e8 |
completed | May 9, 2026, 5:39 a.m. |
Created at: April 10, 2026, 3:09 a.m.