Triple
T9955546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prinz |
E195436
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Peter 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: Peter Prinz | Statement: [Prinz, hasNotableBearer, Peter Prinz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Prinz Context triple: [Prinz, hasNotableBearer, Peter Prinz]
-
A.
Thomas Prinz
Thomas Prinz is a notable individual who shares the surname Prinz and is recognized for his distinct contributions or public presence associated with that name.
-
B.
Michael Prinz
Michael Prinz is a person notable enough to be recognized as a prominent bearer of the surname Prinz.
-
C.
Prinz
chosen
Prinz is a German surname borne by various notable individuals, including figures in politics, religion, and the arts.
-
D.
Prinze
Prinze is the surname of American actor Freddie Prinze Jr., associated with a family of entertainers in film and television.
-
E.
Simon Gratz
Simon Gratz was a prominent Philadelphia lawyer, civic leader, and education advocate in the late 19th and early 20th centuries.
- 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_69ca82eaaa008190a54fa1a9f954b9ad |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb69631d08190ab2b1d1c22d46da7 |
completed | April 2, 2026, 12:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d269ef79548190ac87851efffa3f12 |
completed | April 5, 2026, 1:55 p.m. |
Created at: March 30, 2026, 8:46 p.m.