Triple
T16502890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Magpie |
E400841
|
entity |
| Predicate | appliesTo |
P1129
|
FINISHED |
| Object | German river name "Schwarze Elster" |
E866000
|
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: German river name "Schwarze Elster" | Statement: [Black Magpie, appliesTo, German river name "Schwarze Elster"]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: German river name "Schwarze Elster" Context triple: [Black Magpie, appliesTo, German river name "Schwarze Elster"]
-
A.
River Schwarze Elster
chosen
The River Schwarze Elster is a river in eastern Germany that flows through Saxony, Brandenburg, and Saxony-Anhalt before joining the River Spree.
-
B.
Elbsche
Elbsche is a small river in North Rhine-Westphalia, Germany, that flows through the city of Witten and its surrounding region.
-
C.
Schwarza (tributary of the Rhine)
Schwarza is a small river in the Black Forest region of Germany that serves as a tributary of the Rhine.
-
D.
Schwarzburger
A Schwarzburger was a citizen or native of the former small German state of Schwarzburg-Rudolstadt.
-
E.
Schwarzbach
Schwarzbach is a river in southwestern Germany that flows through the town of Zweibrücken in the state of Rhineland-Palatinate.
- 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_69d88381f6148190819958a038be990e |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e50436c8190836a1bc2baa188b1 |
completed | April 18, 2026, 7:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00582e6e288190825af8758097e325 |
completed | May 10, 2026, 10:04 a.m. |
Created at: April 10, 2026, 5:14 a.m.