Triple
T11843270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rotenburg (Wümme) |
E281706
|
entity |
| Predicate | locatedOnRiver |
P165
|
FINISHED |
| Object | Wümme |
E668618
|
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: Wümme | Statement: [Rotenburg (Wümme), locatedOnRiver, Wümme]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wümme Context triple: [Rotenburg (Wümme), locatedOnRiver, Wümme]
-
A.
Wümme
chosen
The Wümme is a river in northern Germany that flows through Lower Saxony and Bremen before joining with the Hamme to form the Lesum.
-
B.
Schlei
Schlei is a narrow Baltic Sea inlet in northern Germany that resembles a river and is known for its scenic landscapes and historic towns.
-
C.
Dahme
The Dahme is a river in eastern Germany that flows through Brandenburg and Berlin before joining the Spree.
-
D.
Dahme
Dahme is a small coastal town on the Baltic Sea in northern Germany, known for its beaches and seaside tourism.
-
E.
river Hönne
The river Hönne is a small river in North Rhine-Westphalia, Germany, known for flowing through the Sauerland region and the town of Menden, with notable limestone gorges and caves along its course.
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a65a597c8190b09f57463b279afc |
completed | April 10, 2026, 7:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f1679729c08190a9f6750586f90d8d |
completed | April 29, 2026, 2:06 a.m. |
Created at: April 8, 2026, 9:43 p.m.