Triple
T3747168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mauser |
E81236
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Mauser family |
E81236
|
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: Mauser family | Statement: [Mauser, namedAfter, Mauser family]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mauser family Context triple: [Mauser, namedAfter, Mauser family]
-
A.
Krupp family
The Krupp family is a prominent German industrial dynasty historically known for its powerful steel and armaments empire centered in Essen.
-
B.
Mauser
chosen
Mauser is a historic German arms manufacturer renowned for its influential bolt-action rifles and other military firearms.
-
C.
Braun family
The Braun family was a German family best known for including Eva Braun, the longtime companion and brief wife of Adolf Hitler, and her sisters such as Ilse Braun.
-
D.
Foellinger family
The Foellinger family is a philanthropic family known for their significant contributions to educational and cultural institutions, particularly at the University of Illinois.
-
E.
Gütermann family
The Gütermann family is a notable German industrial family best known for its long-standing involvement in the textile and thread manufacturing industry.
- 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_69ad8b19b7b08190a6188804e99c53e9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb69887c8190a3f1188ec85727b0 |
completed | March 8, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4db2f5e9881908c10feafbb569f48 |
completed | March 14, 2026, 3:51 a.m. |
Created at: March 8, 2026, 3:35 p.m.