Triple
T2212325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DAK |
E50945
|
entity |
| Predicate | notableCommander |
P1197
|
FINISHED |
| Object | Ludwig Crüwell |
E107309
|
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: Ludwig Crüwell | Statement: [DAK, notableCommander, Ludwig Crüwell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ludwig Crüwell Context triple: [DAK, notableCommander, Ludwig Crüwell]
-
A.
Ludwig Crüwell
chosen
Ludwig Crüwell was a German Wehrmacht general and Afrika Korps commander during World War II, noted for his leadership in the North African campaign.
-
B.
Fritz von Tarlenheim
Fritz von Tarlenheim is a loyal and courageous young nobleman who aids Rudolf Rassendyll in Anthony Hope’s adventure novel "The Prisoner of Zenda."
-
C.
Josef Jennewein
Josef Jennewein was a German World War II Luftwaffe fighter ace and former Olympic alpine skier.
-
D.
Hermann Blankenstein
Hermann Blankenstein was a prominent 19th-century German architect best known for designing numerous public buildings in Berlin, particularly schools and administrative structures.
-
E.
Franz von Holzhausen
Franz von Holzhausen is an American automobile designer best known as Tesla’s chief designer, responsible for the styling of vehicles such as the Model S, Model 3, Model X, Model Y, and the Cybertruck.
- 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_69a88b06709c8190978fb2418470d1b6 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbfecea6c8190b762bbfda8490e31 |
completed | March 7, 2026, 6:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc01a30608190839f9e11db0f7def |
completed | March 10, 2026, 6:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.