Triple
T19578951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Klaus Schwarzkopf |
E489933
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object | Bochum |
—
|
NE NERFINISHED |
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: Bochum | Statement: [Klaus Schwarzkopf, placeOfDeath, Bochum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bochum Context triple: [Klaus Schwarzkopf, placeOfDeath, Bochum]
-
A.
Bochum
chosen
Bochum is a major city in Germany’s Ruhr region known for its industrial heritage, cultural institutions, and large university.
-
B.
Gelsenkirchen
Gelsenkirchen is a city in western Germany known for its strong football culture and modern stadium, Veltins-Arena, home to FC Schalke 04.
-
C.
Krefeld
Krefeld is a city in western Germany near the Rhine River, known historically for its textile and silk industry.
-
D.
Recklinghausen
Recklinghausen is a city in the Ruhr area of North Rhine-Westphalia, western Germany, known historically for coal mining and its role as a regional administrative center.
-
E.
Mülheim an der Ruhr
Mülheim an der Ruhr is a city in western Germany’s Ruhr area, known for its industrial heritage, riverside setting on the Ruhr River, and role as a regional economic and cultural center.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6402693d88190a828c0e136895783 |
completed | April 20, 2026, 3:03 p.m. |
Created at: April 10, 2026, 1:42 p.m.