Triple
T10018081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joachim Prinz |
E199546
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Prinz |
E195436
|
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: Prinz | Statement: [Joachim Prinz, familyName, Prinz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Prinz Context triple: [Joachim Prinz, familyName, Prinz]
-
A.
Prinz
chosen
Prinz is a German surname borne by various notable individuals, including figures in politics, religion, and the arts.
-
B.
Prinze
Prinze is the surname of American actor Freddie Prinze Jr., associated with a family of entertainers in film and television.
-
C.
Príncipe
Príncipe is the smaller, less-populated island of the Central African island nation of São Tomé and Príncipe, known for its lush rainforests, biodiversity, and status as a UNESCO Biosphere Reserve.
-
D.
König
König is a German-language surname borne by numerous individuals, including notable figures in fields such as religion, science, and the arts.
-
E.
Le Prince
Le Prince is a French surname most notably associated with Jean-Baptiste Le Prince, an 18th-century painter and etcher known for his scenes inspired by travels in Russia.
- 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_69ca8315a1a08190ab310f25620f362b |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd4de1588190a89ed575cff0b8c9 |
completed | April 2, 2026, 1:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2821b22488190913d743bc40a4c8e |
completed | April 5, 2026, 3:39 p.m. |
Created at: March 30, 2026, 8:53 p.m.