Triple
T22546899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Ropers |
E557451
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Jenny
Jenny is a minor character from the sitcom spin-off "The Ropers," which followed the lives of the landlords from "Three's Company."
|
E1541367
|
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: Jenny | Statement: [The Ropers, character, Jenny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jenny Context triple: [The Ropers, character, Jenny]
-
A.
Jenny
Jenny is the main character of the story "Mosquitoes," around whom the narrative and its central events revolve.
-
B.
Jenny
Jenny is a central character in Patrick Hamilton's novel "Twenty Thousand Streets Under the Sky," known as a young barmaid whose beauty and elusive affections profoundly affect the protagonist.
-
C.
Jenny
"Jenny" is a song by the American rock band Soul.
-
D.
Jenny
"Jenny" is a narrative poem by Dante Gabriel Rossetti that explores themes of desire, morality, and Victorian attitudes toward prostitution through a reflective monologue addressed to a fallen woman.
-
E.
Jenny
Jenny is a common feminine given name used in English-speaking countries, often as a diminutive of Jennifer.
- 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: Jenny Triple: [The Ropers, character, Jenny]
Generated description
Jenny is a minor character from the sitcom spin-off "The Ropers," which followed the lives of the landlords from "Three's Company."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jenny Target entity description: Jenny is a minor character from the sitcom spin-off "The Ropers," which followed the lives of the landlords from "Three's Company."
-
A.
Jenny
Jenny is a central fictional character in the Australian television drama series "The Newsreader," which follows the turbulent personal and professional lives of broadcast journalists in the 1980s.
-
B.
Jenny
"Jenny" is a television series associated with Heather Dubrow, known for featuring her in a prominent role.
-
C.
Jenny
Jenny is a fictional character played by American actress Michelle Trachtenberg, known for her roles in film and television.
-
D.
Jenny
Jenny is a central character in the 2004 teen comedy film "EuroTrip," which follows a group of friends on a chaotic adventure across Europe.
-
E.
Jenny
Jenny is a character from the traditional Scottish song "Comin' Thro' the Rye," often depicted as a carefree young woman associated with themes of love and rural life.
- 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_69e11e58662081909ae346ab384514ca |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f366f208190abbc6eb4780b2d48 |
completed | April 29, 2026, 1:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b1deccca48190aba8c7913a769101 |
completed | May 18, 2026, 2:10 p.m. |
| NEDg | Description generation | batch_6a0b1e9bb68481909945905b369247f0 |
completed | May 18, 2026, 2:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b1efb36ac8190a4a9c3005ee58d23 |
completed | May 18, 2026, 2:15 p.m. |
Created at: April 16, 2026, 8:52 p.m.