Triple
T7849139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Nanny |
E181999
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Lauren Lane
Lauren Lane is an American television and stage actress best known for playing the sophisticated and sarcastic C.C. Babcock on the 1990s sitcom "The Nanny."
|
E701679
|
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: Lauren Lane | Statement: [The Nanny, starring, Lauren Lane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lauren Lane Context triple: [The Nanny, starring, Lauren Lane]
-
A.
Lauren Barnes
Lauren Barnes is an American professional soccer defender best known for her standout career with OL Reign in the National Women's Soccer League.
-
B.
Lauren Lloyd
Lauren Lloyd is a film producer best known for her work on the 1990 coming-of-age drama "Mermaids."
-
C.
Lauren
Lauren is a central female protagonist in the romantic comedy film "Think Like a Man," portrayed as a successful, relationship-seeking woman whose love life is influenced by Steve Harvey’s dating advice.
-
D.
Lauren
Lauren is a central character in the musical "Kinky Boots," known as a quirky, down-to-earth factory worker who becomes a key ally and love interest to the protagonist.
-
E.
Lauren
Lauren is a common given name used for people of any gender in various English-speaking and other countries.
- 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: Lauren Lane Triple: [The Nanny, starring, Lauren Lane]
Generated description
Lauren Lane is an American television and stage actress best known for playing the sophisticated and sarcastic C.C. Babcock on the 1990s sitcom "The Nanny."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lauren Lane Target entity description: Lauren Lane is an American television and stage actress best known for playing the sophisticated and sarcastic C.C. Babcock on the 1990s sitcom "The Nanny."
-
A.
Lauren Barnes
Lauren Barnes is an American professional soccer defender best known for her standout career with OL Reign in the National Women's Soccer League.
-
B.
Lauren Lloyd
Lauren Lloyd is a film producer best known for her work on the 1990 coming-of-age drama "Mermaids."
-
C.
Lauren
Lauren is a central female protagonist in the romantic comedy film "Think Like a Man," portrayed as a successful, relationship-seeking woman whose love life is influenced by Steve Harvey’s dating advice.
-
D.
Lauren
Lauren is a central character in the musical "Kinky Boots," known as a quirky, down-to-earth factory worker who becomes a key ally and love interest to the protagonist.
-
E.
Lauren
Lauren is a common given name used for people of any gender in various English-speaking and other countries.
- 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_69cbdf1834b08190ab9fd79387e496a7 |
completed | March 31, 2026, 2:50 p.m. |
| NEDg | Description generation | batch_69cbe309518481909b0857271cb27ab0 |
completed | March 31, 2026, 3:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc05e055588190a5680c4416631c32 |
completed | March 31, 2026, 5:35 p.m. |
Created at: March 30, 2026, 4:50 p.m.