Triple
T15987698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luke and Laura wedding |
E387738
|
entity |
| Predicate | hasActor |
P1668
|
FINISHED |
| Object | Genie Francis |
E995373
|
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: Genie Francis | Statement: [Luke and Laura wedding, hasActor, Genie Francis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Genie Francis Context triple: [Luke and Laura wedding, hasActor, Genie Francis]
-
A.
Genie Francis
chosen
Genie Francis is an American actress best known for her iconic role as Laura Spencer on the long-running soap opera "General Hospital."
-
B.
Jorja Fox
Jorja Fox is an American actress best known for her long-running role as Sara Sidle on the television series CSI: Crime Scene Investigation.
-
C.
Chynna Phillips
Chynna Phillips is an American singer and actress best known as a member of the pop group Wilson Phillips.
-
D.
Melissa Cobb
Melissa Cobb is an American film producer best known for her work on major animated features, including the Kung Fu Panda franchise.
-
E.
Leslie Charleson
Leslie Charleson is an American actress best known for her long-running role as Monica Quartermaine on the soap opera "General Hospital."
- 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1575993948190a05d60fc9d0c05fa |
completed | April 16, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00456d5e74819080c838468ec015ef |
completed | May 10, 2026, 8:44 a.m. |
Created at: April 10, 2026, 4:54 a.m.