Triple
T7500556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lesum |
E177246
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object | Hamme |
E550185
|
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: Hamme | Statement: [Lesum, hasTributary, Hamme]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hamme Context triple: [Lesum, hasTributary, Hamme]
-
A.
Hamme
Hamme is a municipality in East Flanders, Belgium, known for its location along the Scheldt River and its blend of residential areas and natural landscapes.
-
B.
Hohne
Hohne is a village in Lower Saxony, Germany, historically notable for its military garrison and association with British Army units.
-
C.
Nyhausen
Nyhausen is a locality in Germany historically noted as the birthplace of the Swedish nobleman and soldier Philip Christoph von Königsmarck.
-
D.
Holtemme
chosen
The Holtemme is a small river in the Harz region of Saxony-Anhalt, Germany, flowing through towns such as Wernigerode before joining the Bode.
-
E.
Wiehe
Wiehe is a small town in the German state of Thuringia, historically notable as the birthplace of the influential 19th-century historian Leopold von Ranke.
- 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_69c69f2696688190915a8458f2398211 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f59aabb8819085bdbe9c793d5b8b |
completed | March 27, 2026, 9:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c84608021481908ce58a131d75188b |
completed | March 28, 2026, 9:20 p.m. |
Created at: March 27, 2026, 3:44 p.m.