Triple
T6860311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Salzdetfurth |
E158259
|
entity |
| Predicate | locatedOnRiver |
P165
|
FINISHED |
| Object | Lamme |
E379325
|
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: Lamme | Statement: [Bad Salzdetfurth, locatedOnRiver, Lamme]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lamme Context triple: [Bad Salzdetfurth, locatedOnRiver, Lamme]
-
A.
Lamme
chosen
Lamme is a small river in Lower Saxony, Germany, that serves as a tributary of the Innerste.
-
B.
Lamme
Lamme was an influential figure in electrical engineering whose legacy is honored by the AIEE Lamme Medal.
-
C.
Lomme
Lomme is a suburban district and former commune that now forms part of the metropolitan area of Lille in northern France.
-
D.
Liskamm
Liskamm is a prominent and notoriously corniced mountain in the Pennine Alps on the Swiss–Italian border, known for its sharp ridges and challenging climbing conditions.
-
E.
Karosta
Karosta is a historic former military port district in the Latvian city of Liepāja, known for its Tsarist-era fortifications, Soviet naval heritage, and distinctive coastal landscape.
- 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_69c68830cdbc8190a8301c7a9d9f651a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d8737fac81909fc546ca2bf6a278 |
completed | March 27, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c72fe79af081909baacbfd4d5e8f24 |
completed | March 28, 2026, 1:33 a.m. |
Created at: March 27, 2026, 2:21 p.m.