Triple
T7849156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Nanny |
E181999
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Niles
Niles is the witty, sarcastic butler from the sitcom "The Nanny," known for his sharp one-liners and ongoing rivalry with C.C. Babcock.
|
E699899
|
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: Niles | Statement: [The Nanny, mainCharacter, Niles]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Niles Context triple: [The Nanny, mainCharacter, Niles]
-
A.
Niles
Niles is a historic former town in California, now a district of Fremont, known for its early silent film industry and railroad heritage.
-
B.
Trent
The Trent is one of the principal rivers in England, flowing through the Midlands and joining the Humber estuary before reaching the North Sea.
-
C.
Gustavus
Gustavus is a Latinized masculine given name historically borne by several Swedish kings and used in various European and English-speaking contexts.
-
D.
Leland
Leland is a masculine given name of English origin, historically associated with figures such as American industrialist and Stanford University founder Leland Stanford.
-
E.
Qualley
Qualley is the surname of an American family best known for actress and model Margaret Qualley and her mother, actress Andie MacDowell.
- 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: Niles Triple: [The Nanny, mainCharacter, Niles]
Generated description
Niles is the witty, sarcastic butler from the sitcom "The Nanny," known for his sharp one-liners and ongoing rivalry with C.C. Babcock.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Niles Target entity description: Niles is the witty, sarcastic butler from the sitcom "The Nanny," known for his sharp one-liners and ongoing rivalry with C.C. Babcock.
-
A.
Niles
Niles is a historic former town in California, now a district of Fremont, known for its early silent film industry and railroad heritage.
-
B.
Trent
The Trent is one of the principal rivers in England, flowing through the Midlands and joining the Humber estuary before reaching the North Sea.
-
C.
Gustavus
Gustavus is a Latinized masculine given name historically borne by several Swedish kings and used in various European and English-speaking contexts.
-
D.
Leland
Leland is a masculine given name of English origin, historically associated with figures such as American industrialist and Stanford University founder Leland Stanford.
-
E.
Qualley
Qualley is the surname of an American family best known for actress and model Margaret Qualley and her mother, actress Andie MacDowell.
- 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.