Triple
T15757576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Innerste |
E382006
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Bad Salzdetfurth |
E158259
|
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 Salzdetfurth | Statement: [Innerste, flowsThrough, Bad Salzdetfurth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Salzdetfurth Context triple: [Innerste, flowsThrough, Bad Salzdetfurth]
-
A.
Bad Salzdetfurth
chosen
Bad Salzdetfurth is a spa town in Lower Saxony, Germany, known for its historic saltworks and therapeutic health resorts.
-
B.
Bad Salzungen
Bad Salzungen is a spa town in Thuringia, Germany, known for its saline springs and therapeutic health resorts.
-
C.
Bad Salzdetfurth, Germany
Bad Salzdetfurth is a spa town in Lower Saxony, Germany, known for its saline springs, health resorts, and historic half-timbered architecture.
-
D.
Bad Langensalza
Bad Langensalza is a historic spa town in Thuringia, Germany, known for its thermal baths, well-preserved old town, and numerous themed gardens.
-
E.
Othmarschen
Othmarschen is a residential district in the west of Hamburg, Germany, known for its affluent neighborhoods, green spaces, and location along the Elbe River.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b1ff4881909d5240d1d30f5c8b |
completed | April 16, 2026, 3 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff877311dc8190b55fe7ca5c0843da |
completed | May 9, 2026, 7:13 p.m. |
Created at: April 10, 2026, 4:47 a.m.