Triple
T27224394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grace Gealey |
E681368
|
entity |
| Predicate | marriagePartnerInSameShow |
P140690
|
FINISHED |
| Object | Trai Byers |
—
|
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: Trai Byers | Statement: [Grace Gealey, marriagePartnerInSameShow, Trai Byers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriagePartnerInSameShow Context triple: [Grace Gealey, marriagePartnerInSameShow, Trai Byers]
-
A.
hasSpouseInTVSeries
chosen
Indicates that one person is the spouse of another person within the context of a specific TV series.
-
B.
hasSpouseActorsInLeads
Indicates that the primary leading roles in a work are performed by actors who are spouses of each other.
-
C.
spouseAppearsIn
Indicates that the spouse of a given person appears or is featured in a specified work, context, or setting.
-
D.
romanticPartnerInSeries
Indicates that one character is portrayed as a romantic partner of another character within the context of a specific series or narrative.
-
E.
resultedInMarriageTo
Indicates that one event, action, or circumstance led to or caused a marriage to occur between the related entities.
- F. None of above.
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_69eefac9f64c8190a07490fe0c8b72a3 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d17e8d48190b30bcc2f4bd81eb2 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 27, 2026, 9:44 a.m.