Triple
T23295677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reba |
E590161
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Kyra Hart |
—
|
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: Kyra Hart | Statement: [Reba, hasCharacter, Kyra Hart]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kyra Hart Context triple: [Reba, hasCharacter, Kyra Hart]
-
A.
Kyra Hart
chosen
Kyra Hart is a fictional character from the American sitcom "Reba," known as Reba's witty and often sarcastic middle child.
-
B.
Kyra Devore
Kyra Devore is a pivotal ghostly character in Stephen King’s novel "Bag of Bones," whose tragic past and supernatural presence drive much of the story’s mystery and horror.
-
C.
Kyra Nichols
Kyra Nichols is an acclaimed American ballerina best known as one of the leading principal dancers of New York City Ballet during the late 20th century.
-
D.
Kyra
Kyra is a feminine given name most notably borne by American actress and producer Kyra Sedgwick.
-
E.
Kyra Hollis
Kyra Hollis is the idealistic young woman at the center of David Hare’s play "Skylight," whose complex relationship with an older former lover drives the drama’s exploration of love, class, and moral responsibility.
- 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_69e25d1af9d88190a0b9b5e8fa608618 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196cec9e88190b83cfd53a6455e0f |
completed | April 29, 2026, 5:27 a.m. |
Created at: April 17, 2026, 5:03 p.m.