Triple
T19789483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donna Logan |
E475370
|
entity |
| Predicate | childWith |
P6882
|
FINISHED |
| Object | Justin Barber |
—
|
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: Justin Barber | Statement: [Donna Logan, childWith, Justin Barber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Justin Barber Context triple: [Donna Logan, childWith, Justin Barber]
-
A.
Justin Barber
Justin Barber is a film producer known for his work on the independent romantic drama "Medicine for Melancholy."
-
B.
Justin Barber
chosen
Justin Barber is a fictional character from the soap opera "The Bold and the Beautiful," known as a savvy attorney and loyal right-hand man to media mogul Bill Spencer Jr.
-
C.
Sterling Marlin
Sterling Marlin is an American former NASCAR driver best known for winning back-to-back Daytona 500s in the mid-1990s.
-
D.
Dale Jarrett
Dale Jarrett is a retired American NASCAR driver and 1999 Cup Series champion, best known for winning the Daytona 500 three times.
-
E.
Scott Sharp
Scott Sharp is an American former race car driver best known for competing in the IndyCar Series and winning the 1996 Indy Racing League co-championship.
- 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_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6538ae5108190b80eb7de6f445f02 |
completed | April 20, 2026, 4:25 p.m. |
Created at: April 10, 2026, 1:49 p.m.