Triple
T15201112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruppert |
E363268
|
entity |
| Predicate | hasSurnameForm |
P18
|
FINISHED |
| Object | Ruppert |
E363268
|
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: Ruppert | Statement: [Ruppert, hasSurnameForm, Ruppert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ruppert Context triple: [Ruppert, hasSurnameForm, Ruppert]
-
A.
Ruppert
chosen
Ruppert is a masculine given name and surname of Germanic origin, related to the name Rupert.
-
B.
Roone
Roone is a masculine given name most notably associated with pioneering American television sports and news executive Roone Arledge.
-
C.
Reeser
Reeser is a surname most notably associated with American actress Autumn Reeser, known for her roles in television and film.
-
D.
Rudy Bond
Rudy Bond was an American character actor known for his supporting roles in mid-20th-century films and stage productions.
-
E.
Ruettiger
Ruettiger is the surname of Rudy Ruettiger, the former Notre Dame football player whose life inspired the popular sports film "Rudy."
- 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006b588b88190a88e91d521acbdfe |
completed | April 15, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fedd2dc6f08190a8f1612ac29a8654 |
completed | May 9, 2026, 7:07 a.m. |
Created at: April 10, 2026, 3:10 a.m.