Triple
T5377738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Main |
E113003
|
entity |
| Predicate | majorRightTributary |
P415
|
FINISHED |
| Object | Tauber |
E413664
|
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: Tauber | Statement: [Main, majorRightTributary, Tauber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tauber Context triple: [Main, majorRightTributary, Tauber]
-
A.
Tauber
chosen
The Tauber is a river in central Germany that flows through the Franconian region, including the spa town of Bad Mergentheim, before joining the Main River.
-
B.
Miltenberg
Miltenberg is a historic town in Bavaria, Germany, known for its well-preserved medieval old town along the Main River and its timber-framed architecture.
-
C.
Sieber
Sieber is a small river in the German state of Lower Saxony that flows through the Harz Mountains and into the Oder.
-
D.
Geva
Geva is a surname most notably associated with Tamara Geva, a Russian-American actress, dancer, and choreographer.
-
E.
Tureberg
Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
- 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_69bd4436a1988190af18dcff7fd306b4 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd86cb13ac81909dc364e7d3605844 |
completed | March 20, 2026, 5:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf29428cec8190a20bea8fcae59d8f |
completed | March 21, 2026, 11:26 p.m. |
Created at: March 20, 2026, 2:03 p.m.