Triple
T13695058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Million Little Things |
E328362
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Dana Honor |
E565458
|
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: Dana Honor | Statement: [A Million Little Things, executiveProducer, Dana Honor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dana Honor Context triple: [A Million Little Things, 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.
Danna
Danna is the surname of Mychael Danna, a Canadian composer renowned for his innovative and atmospheric film scores.
-
D.
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."
-
E.
Dana Ballard
Dana Ballard is an American computer scientist and cognitive scientist known for his pioneering work in computational vision and models of human perception and cognition.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc8773f388190b2413b1e05fd5fd7 |
completed | April 12, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f794514afc8190b334b1fc74a6cdd5 |
completed | May 3, 2026, 6:30 p.m. |
Created at: April 9, 2026, 9:54 p.m.