Triple
T19492447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | district of Waldshut |
E487684
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Tiengen |
—
|
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: Tiengen | Statement: [district of Waldshut, containsTown, Tiengen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tiengen Context triple: [district of Waldshut, containsTown, Tiengen]
-
A.
Tiengen
chosen
Tiengen is a district of the German town Waldshut-Tiengen in Baden-Württemberg, known for its historic old town and location near the Swiss border.
-
B.
Tönning
Tönning is a historic town in northern Germany’s Schleswig-Holstein region, known for its strategic location on the Eider River and its former role as a fortified port.
-
C.
Gerlitzen
Gerlitzen is a popular mountain and ski area in Carinthia, Austria, known for its panoramic views over the Ossiacher See and the surrounding Alps.
-
D.
Triberg
Triberg is a picturesque German town in the Black Forest, renowned for its towering waterfalls and traditional cuckoo clocks.
-
E.
Villingen
Villingen is a historic German town in the Black Forest region, now part of the twin city of Villingen-Schwenningen in the state of Baden-Württemberg.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6348f4d708190a6e612863fee4b97 |
completed | April 20, 2026, 2:13 p.m. |
Created at: April 10, 2026, 1:39 p.m.