Triple
T7792671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Werre |
E180218
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Bad Salzuflen |
E575701
|
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 Salzuflen | Statement: [Werre, flowsThrough, Bad Salzuflen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Salzuflen Context triple: [Werre, flowsThrough, Bad Salzuflen]
-
A.
Bad Salzuflen
chosen
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.
-
B.
Bad Salzungen
Bad Salzungen is a spa town in Thuringia, Germany, known for its saline springs and therapeutic health resorts.
-
C.
Bad Rothenfelde
Bad Rothenfelde is a spa town in Lower Saxony, Germany, known for its saline springs and health resort facilities.
-
D.
Bad Cannstatt
Bad Cannstatt is a historic district of Stuttgart, Germany, known for its mineral springs, traditional architecture, and the Cannstatter Volksfest beer festival.
-
E.
Bad Münstereifel
Bad Münstereifel is a historic spa town in the Eifel region of North Rhine-Westphalia, western Germany, known for its well-preserved medieval center and fortifications.
- 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_69ca827d22208190b4dc5aa680edcf5d |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cae938714c8190b89917e6ded004da |
completed | March 30, 2026, 9:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbdeb6c1b88190a38fb4507bfb380c |
completed | March 31, 2026, 2:48 p.m. |
Created at: March 30, 2026, 4:30 p.m.