Triple
T19710846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Me, Myself & I |
E473339
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Dana Honor |
—
|
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: Dana Honor | Statement: [Me, Myself & I, executiveProducer, Dana Honor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dana Honor Context triple: [Me, Myself & I, executiveProducer, Dana Honor]
-
A.
Dana Honor
chosen
Dana Honor is a television producer best known for her work as an executive producer on comedy series such as "HouseBroken."
-
B.
Dana Isaiah
Dana Isaiah is an American fitness model and personal trainer best known as the husband of singer and actress Jordin Sparks.
-
C.
Dana Sano
Dana Sano is a music professional best known for her work on the soundtrack of the film "Little Odessa."
-
D.
Danna
Danna is the surname of Mychael Danna, a Canadian composer renowned for his innovative and atmospheric film scores.
-
E.
Dana Dane
Dana Dane is an American rapper and storyteller known for his humorous narrative style and influential 1980s hip-hop tracks like "Cinderfella Dana Dane."
- 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_69d8e516dd048190a0b6c93ea3e71f58 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e64407ed208190944ae43b5e44bbdc |
completed | April 20, 2026, 3:19 p.m. |
Created at: April 10, 2026, 1:46 p.m.