Triple
T1829091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Renk HSWL 354 |
E40719
|
entity |
| Predicate | developedBy |
P73
|
FINISHED |
| Object | Renk AG |
E203401
|
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: Renk AG | Statement: [Renk HSWL 354, developedBy, Renk AG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Renk AG Context triple: [Renk HSWL 354, developedBy, Renk AG]
-
A.
Renk AG
chosen
Renk AG is a German engineering company specializing in high-performance transmissions, gear units, and drive technology for military and industrial applications.
-
B.
Borsigwerke
Borsigwerke is a Berlin U-Bahn station on line U6 serving the Tegel district in the city’s northwest.
-
C.
Erla Maschinenwerk
Erla Maschinenwerk was a German aircraft manufacturing company best known for producing Messerschmitt fighter planes under license during World War II.
-
D.
Krauss-Maffei Wegmann
Krauss-Maffei Wegmann is a German defense company specializing in the design and production of armored vehicles and military land systems.
-
E.
Traton
Traton is a commercial vehicle manufacturer and holding company that oversees brands like MAN and Scania within the Volkswagen Group.
- 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_69a8864644bc8190b2358ab897194ac1 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb012e174819090c188e55a9812b4 |
completed | March 7, 2026, 4:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adc9b24f448190a3aa5a85a9106d71 |
completed | March 8, 2026, 7:10 p.m. |
Created at: March 4, 2026, 7:32 p.m.