Triple
T7849138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Nanny |
E181999
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Daniel Davis
Daniel Davis is an American actor best known for his role as the witty butler Niles on the sitcom "The Nanny."
|
E699892
|
NE FINISHED |
How this triple was built (4 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: Daniel Davis | Statement: [The Nanny, starring, Daniel Davis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Davis Context triple: [The Nanny, starring, Daniel Davis]
-
A.
Jeremy Davis
Jeremy Davis is an American bassist best known for being a founding member and longtime bassist of the rock band Paramore.
-
B.
Michael Davis
Michael Davis is an entrepreneur best known as a co-founder of Bomis, the web portal company that played a key role in the early development of Wikipedia.
-
C.
Michael Davis
Michael Davis is an American comic book artist, writer, and producer best known as one of the founding members of the influential, Black-owned comics company Milestone Media.
-
D.
Ryan Davis
Ryan Davis is a Ruby developer best known for creating the Minitest testing framework.
-
E.
Kevin Davis
Kevin Davis is a Canadian municipal politician who serves as the mayor of Brantford, Ontario.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Daniel Davis Triple: [The Nanny, starring, Daniel Davis]
Generated description
Daniel Davis is an American actor best known for his role as the witty butler Niles on the sitcom "The Nanny."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Daniel Davis Target entity description: Daniel Davis is an American actor best known for his role as the witty butler Niles on the sitcom "The Nanny."
-
A.
Jeremy Davis
Jeremy Davis is an American bassist best known for being a founding member and longtime bassist of the rock band Paramore.
-
B.
Michael Davis
Michael Davis is an entrepreneur best known as a co-founder of Bomis, the web portal company that played a key role in the early development of Wikipedia.
-
C.
Michael Davis
Michael Davis is an American comic book artist, writer, and producer best known as one of the founding members of the influential, Black-owned comics company Milestone Media.
-
D.
Ryan Davis
Ryan Davis is a Ruby developer best known for creating the Minitest testing framework.
-
E.
Kevin Davis
Kevin Davis is a Canadian municipal politician who serves as the mayor of Brantford, Ontario.
- F. None of above. chosen
Provenance (5 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_69ca82869ee08190b8f9040dbc2c0467 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb18e989ac819090e459b77d8932d3 |
completed | March 31, 2026, 12:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5b0515c08190b866a39749d54849 |
completed | March 31, 2026, 5:26 a.m. |
| NEDg | Description generation | batch_69cb762eab0881909c5035b3086dfdd9 |
completed | March 31, 2026, 7:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cbb801cc0c8190864d28e199eb5e67 |
completed | March 31, 2026, 12:03 p.m. |
Created at: March 30, 2026, 4:50 p.m.