Triple
T11843581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fritz X |
E281715
|
entity |
| Predicate | developer |
P73
|
FINISHED |
| Object | Ruhrstahl |
E949232
|
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: Ruhrstahl | Statement: [Fritz X, developer, Ruhrstahl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ruhrstahl Context triple: [Fritz X, developer, Ruhrstahl]
-
A.
Ruhrstahl
chosen
Ruhrstahl was a German armaments manufacturer best known for producing advanced World War II munitions and guided weapons.
-
B.
Oerlikon
Oerlikon is a district in the north of Zurich, Switzerland, known as a major residential, commercial, and transportation hub of the city.
-
C.
Steyr
Steyr is a historic industrial city in northern Austria known for its well-preserved old town and long tradition of metalworking and manufacturing.
-
D.
Rheinmetall
Rheinmetall is a major German defense and automotive company best known for producing advanced military technologies, including the main armament and systems for modern battle tanks.
-
E.
Diehl
Diehl is the middle name of Newton D. Baker, an American lawyer and politician who served as U.S. Secretary of War during World War I.
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a65a597c8190b09f57463b279afc |
completed | April 10, 2026, 7:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f2814210e48190821fca390dc7e312 |
completed | April 29, 2026, 10:08 p.m. |
Created at: April 8, 2026, 9:43 p.m.