Triple
T6814258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parks and Recreation |
E156712
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Retta |
E319407
|
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: Retta | Statement: [Parks and Recreation, starring, Retta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Retta Context triple: [Parks and Recreation, starring, Retta]
-
A.
Retta
chosen
Retta is an American actress and comedian best known for her roles on the television series "Parks and Recreation" and "Good Girls."
-
B.
Gina Linetti
Gina Linetti is a hilariously self-absorbed, sharp-tongued civilian administrator known for her bizarre confidence and deadpan humor on the sitcom Brooklyn Nine-Nine.
-
C.
Renny
Renny is a diminutive or short form of the given name René, often used as a familiar or affectionate variant.
-
D.
Judi Farr
Judi Farr was an Australian actress known for her extensive work in theatre, film, and television, including prominent roles in classic Australian TV comedies and dramas.
-
E.
Talia Balsam
Talia Balsam is an American actress known for her work in film and television, including roles in series like Mad Men and numerous independent movies.
- 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_69c68828b26c819090fe9df7612bbc27 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d32c40508190932718a649fc1417 |
completed | March 27, 2026, 6:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c748ad80b881909efd0c0abddb95a5 |
completed | March 28, 2026, 3:19 a.m. |
Created at: March 27, 2026, 2:17 p.m.