Triple
T23031904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rectify |
E573483
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Abigail Spencer |
—
|
NE NERFINISHED |
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: Abigail Spencer | Statement: [Rectify, stars, Abigail Spencer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abigail Spencer Context triple: [Rectify, stars, Abigail Spencer]
-
A.
Abigail Spencer
chosen
Abigail Spencer is an American actress known for her roles in television series such as "Mad Men," "Rectify," and "Timeless," as well as various film appearances.
-
B.
Kaya Faison
Kaya Faison is one of the children of the late nurse Lisa Askey and actor Donald Faison.
-
C.
Melissa Fumero
Melissa Fumero is an American actress best known for playing Detective Amy Santiago on the television comedy series "Brooklyn Nine-Nine."
-
D.
Sarah Chalke
Sarah Chalke is a Canadian actress best known for her roles as Dr. Elliot Reid on the sitcom "Scrubs" and Becky Conner on "Roseanne."
-
E.
Kaitlin Olson
Kaitlin Olson is an American actress and comedian best known for playing Dee Reynolds on the long-running sitcom "It's Always Sunny in Philadelphia."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245b911188190bc3d96326c847969 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f184822a90819081907d72c76770b0 |
completed | April 29, 2026, 4:09 a.m. |
Created at: April 17, 2026, 3:53 p.m.