Triple
T12877798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leipzig metropolitan region |
E308012
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Bad Lauchstädt |
E187719
|
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: Bad Lauchstädt | Statement: [Leipzig metropolitan region, containsCity, Bad Lauchstädt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Lauchstädt Context triple: [Leipzig metropolitan region, containsCity, Bad Lauchstädt]
-
A.
Bad Lauchstädt
chosen
Bad Lauchstädt is a historic spa town in the German state of Saxony-Anhalt, known for its classical Kurpark and Goethe-Theater.
-
B.
Bad Rothenfelde
Bad Rothenfelde is a spa town in Lower Saxony, Germany, known for its saline springs and health resort facilities.
-
C.
Bad Heilbrunn
Bad Heilbrunn is a spa municipality in Upper Bavaria, Germany, known for its health resorts and scenic Alpine foothills setting.
-
D.
Bad Säckingen
Bad Säckingen is a historic spa town in southwestern Germany on the Rhine River, known for its medieval old town and one of the longest covered wooden bridges in Europe.
-
E.
Bad Salzuflen
Bad Salzuflen is a German spa town in the Lippe district of North Rhine-Westphalia, known for its saltwater springs and historic half-timbered architecture.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d970fa8474819086a8af3c90f3ca84 |
completed | April 10, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6a55393a88190a88c9357a6db5aec |
completed | May 3, 2026, 1:30 a.m. |
Created at: April 9, 2026, 5:38 p.m.