Triple
T4555630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ernie Johnson Jr. |
E120469
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object | Ashley Johnson |
E304846
|
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: Ashley Johnson | Statement: [Ernie Johnson Jr., hasChild, Ashley Johnson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ashley Johnson Context triple: [Ernie Johnson Jr., hasChild, Ashley Johnson]
-
A.
Ashley Johnson
chosen
Ashley Johnson is an American actress and voice actress known for her roles in television, film, and video games, including voicing Ellie in "The Last of Us" series.
-
B.
Anna Torv
Anna Torv is an Australian actress best known for her lead role as FBI agent Olivia Dunham in the science fiction television series "Fringe."
-
C.
Lauren Ambrose
Lauren Ambrose is an American actress best known for her critically acclaimed role as Claire Fisher on the HBO drama series "Six Feet Under."
-
D.
Alafair Burke
Alafair Burke is an American crime novelist, law professor, and former prosecutor known for her contemporary suspense novels and collaborations on bestselling mystery series.
-
E.
Gina Torres
Gina Torres is an American actress known for her roles in television series such as "Suits," "Firefly," and "Hannibal."
- 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_69bd4636f1648190a701445c2fcd9c17 |
completed | March 20, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69bd5813af948190b10b02dadf6496bf |
completed | March 20, 2026, 2:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdd3a139f08190a0211d5848ccdfad |
completed | March 20, 2026, 11:09 p.m. |
Created at: March 20, 2026, 1:09 p.m.