Triple
T7116705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Friedrich Krupp |
E165837
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Krupp |
E31323
|
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: Krupp | Statement: [Friedrich Krupp, employer, Krupp]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Krupp Context triple: [Friedrich Krupp, employer, Krupp]
-
A.
Krupp (company)
chosen
Krupp (company) was a major German industrial conglomerate best known for its steel production and armaments manufacturing, playing a central role in both World Wars and in the development of heavy industry in Germany.
-
B.
Borsigwerke
Borsigwerke is a Berlin U-Bahn station on line U6 serving the Tegel district in the city’s northwest.
-
C.
Deutsche Werft AG
Deutsche Werft AG was a German shipbuilding company based in Hamburg, known for constructing naval vessels and submarines, particularly during the World War II era.
-
D.
Blohm & Voss
Blohm & Voss is a German shipbuilding and engineering company renowned for constructing major naval vessels and later aircraft, particularly during the World Wars.
-
E.
Henschel & Sohn
Henschel & Sohn was a German engineering and manufacturing company best known for producing heavy military vehicles, including tanks, during World War II.
- 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_69c6888227bc8190a1394679e3116f90 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e617a528819085d4b8e1b5699966 |
completed | March 27, 2026, 8:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7ad86ac688190af97b42d0cb36b84 |
completed | March 28, 2026, 10:29 a.m. |
Created at: March 27, 2026, 2:43 p.m.