Triple
T14766152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Necessary Roughness |
E347000
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Amanda Righetti |
E607527
|
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: Amanda Righetti | Statement: [Necessary Roughness, portrayedBy, Amanda Righetti]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amanda Righetti Context triple: [Necessary Roughness, portrayedBy, Amanda Righetti]
-
A.
Amanda Righetti
chosen
Amanda Righetti is an American actress best known for her role as agent Grace Van Pelt on the television crime drama series "The Mentalist."
-
B.
Amanda Robinson
Amanda Robinson is the spouse of Jason Robinson.
-
C.
Amanda Kelly
Amanda Kelly is a technology entrepreneur best known as a co-founder of Streamlit, an open-source framework for building data and machine learning web apps in Python.
-
D.
Emily Sonnett
Emily Sonnett is an American professional soccer defender and U.S. women's national team player known for her versatility, ball-winning ability, and contributions to multiple NWSL clubs and World Cup–winning squads.
-
E.
Jessica DiCicco
Jessica DiCicco is an American voice actress known for her work in numerous animated television series and films, including roles on shows like Adventure Time and The Loud House.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7f576c881909da70627f5897c94 |
completed | April 14, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0cf68d94819093567bc630f67b60 |
completed | May 8, 2026, 4:19 p.m. |
Created at: April 10, 2026, 1:30 a.m.