Triple
T5664715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moll Flanders |
E124829
|
entity |
| Predicate | hasAdaptation |
P1690
|
FINISHED |
| Object |
The Fortunes and Misfortunes of Moll Flanders (1996 TV series)
The Fortunes and Misfortunes of Moll Flanders (1996 TV series) is a British television drama adaptation of Daniel Defoe’s classic 1722 novel, following the tumultuous life and adventures of the resourceful Moll Flanders.
|
E538808
|
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: The Fortunes and Misfortunes of Moll Flanders (1996 TV series) | Statement: [Moll Flanders, hasAdaptation, The Fortunes and Misfortunes of Moll Flanders (1996 TV series)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Fortunes and Misfortunes of Moll Flanders (1996 TV series) Context triple: [Moll Flanders, hasAdaptation, The Fortunes and Misfortunes of Moll Flanders (1996 TV series)]
-
A.
Moll Flanders
Moll Flanders is a 1722 novel by Daniel Defoe that follows the picaresque life of a resourceful woman who survives through crime, deception, and multiple marriages in 17th-century England.
-
B.
The Pallisers (TV series)
The Pallisers (TV series) is a 1970s BBC television drama based on Anthony Trollope’s political novels, chronicling the intertwined personal and political lives of an aristocratic Victorian family.
-
C.
Good Wives
Good Wives is the 1869 sequel to Louisa May Alcott’s novel Little Women, continuing the story of the March sisters into adulthood, marriage, and early married life.
-
D.
The Fortunes of Men
The Fortunes of Men is an Old English poem that reflects on the unpredictable and varied destinies allotted to humans, preserved in the Exeter Book manuscript.
-
E.
Harlots
Harlots is a British period drama television series set in 18th-century London that explores the lives, rivalries, and struggles of women working in the city’s brothels.
- 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: The Fortunes and Misfortunes of Moll Flanders (1996 TV series) Triple: [Moll Flanders, hasAdaptation, The Fortunes and Misfortunes of Moll Flanders (1996 TV series)]
Generated description
The Fortunes and Misfortunes of Moll Flanders (1996 TV series) is a British television drama adaptation of Daniel Defoe’s classic 1722 novel, following the tumultuous life and adventures of the resourceful Moll Flanders.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: The Fortunes and Misfortunes of Moll Flanders (1996 TV series) Target entity description: The Fortunes and Misfortunes of Moll Flanders (1996 TV series) is a British television drama adaptation of Daniel Defoe’s classic 1722 novel, following the tumultuous life and adventures of the resourceful Moll Flanders.
-
A.
Moll Flanders
Moll Flanders is a 1722 novel by Daniel Defoe that follows the picaresque life of a resourceful woman who survives through crime, deception, and multiple marriages in 17th-century England.
-
B.
The Pallisers (TV series)
The Pallisers (TV series) is a 1970s BBC television drama based on Anthony Trollope’s political novels, chronicling the intertwined personal and political lives of an aristocratic Victorian family.
-
C.
Good Wives
Good Wives is the 1869 sequel to Louisa May Alcott’s novel Little Women, continuing the story of the March sisters into adulthood, marriage, and early married life.
-
D.
The Fortunes of Men
The Fortunes of Men is an Old English poem that reflects on the unpredictable and varied destinies allotted to humans, preserved in the Exeter Book manuscript.
-
E.
Harlots
Harlots is a British period drama television series set in 18th-century London that explores the lives, rivalries, and struggles of women working in the city’s brothels.
- 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_69c00828906881908966f270b8f130cf |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0232497a08190ab7227f0e135a29e |
completed | March 22, 2026, 5:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04dad0af4819088280f2d97173e9e |
completed | March 22, 2026, 8:14 p.m. |
| NEDg | Description generation | batch_69c056a981f881908663c315fe2db829 |
completed | March 22, 2026, 8:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0573ca734819098de3376ff93c309 |
completed | March 22, 2026, 8:55 p.m. |
Created at: March 22, 2026, 3:43 p.m.