Triple
T23295547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Does He Love You |
E590158
|
entity |
| Predicate | originalArtist |
P11499
|
FINISHED |
| Object | Linda Davis |
—
|
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: Linda Davis | Statement: [Does He Love You, originalArtist, Linda Davis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linda Davis Context triple: [Does He Love You, originalArtist, Linda Davis]
-
A.
Linda Davis
chosen
Linda Davis is an American country music singer best known for her Grammy-winning duet "Does He Love You" with Reba McEntire.
-
B.
Linda Stokes
Linda Stokes is an American costume designer best known for her long-term marriage to actor James Caan.
-
C.
Linda Jones
Linda Jones is the daughter of legendary American animator and director Chuck Jones, known for helping preserve and promote his artistic legacy.
-
D.
Lyn Davis
Lyn Davis is best known as the wife of influential American television writer and producer Norman Lear.
-
E.
Linda Larkin
Linda Larkin is an American actress best known for providing the speaking voice of Princess Jasmine in Disney’s animated film "Aladdin" and its related media.
- 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.