Triple
T3204056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scott Rolen |
E67118
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Rolen |
E67118
|
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: Rolen | Statement: [Scott Rolen, familyName, Rolen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rolen Context triple: [Scott Rolen, familyName, Rolen]
-
A.
Rolen
chosen
Rolen is a surname most notably associated with Scott Rolen, a Hall of Fame Major League Baseball third baseman.
-
B.
Rolf
Rolf is a masculine given name of Germanic origin commonly used in German-speaking and Scandinavian countries.
-
C.
Rolph
Rolph is a surname most notably associated with James Rolph, a prominent early 20th-century American politician and former mayor of San Francisco and governor of California.
-
D.
Randolf
Randolf is a surname most notably associated with Danish-American silent film actor Anders Randolf.
-
E.
Royer
Royer was a costume designer known for his work on classic Hollywood films, including the 1939 drama "The Rains Came."
- 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_69ad8589bd988190afa7ed2bdffb7b33 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaa54124c8190a22089ce2eaedab5 |
completed | March 8, 2026, 4:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b24bcbb0e88190b4413c4ba3de0eeb |
completed | March 12, 2026, 5:14 a.m. |
Created at: March 8, 2026, 3:07 p.m.