Triple
T18285469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isn't It Romantic |
E437969
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Janie Blumberg
Janie Blumberg is the aspiring songwriter protagonist of the 1984 romantic comedy film "Isn't It Romantic?".
|
E1397398
|
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: Janie Blumberg | Statement: [Isn't It Romantic, mainCharacter, Janie Blumberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Janie Blumberg Context triple: [Isn't It Romantic, mainCharacter, Janie Blumberg]
-
A.
Nancy Blansky
Nancy Blansky is the central character of the 1970s American sitcom "Blansky's Beauties," portrayed as a seasoned Las Vegas showbiz professional managing a troupe of young performers.
-
B.
Jill Krementz
Jill Krementz is an American photographer and author best known for her portraits of writers and her work in children's literature.
-
C.
Marla Frumkin
Marla Frumkin is an American voice actress best known for portraying Velma Dinkley in the Scooby-Doo animated franchise.
-
D.
Sherri Kramer
Sherri Kramer is an American screenwriter and the former wife of late comedian and actor Bob Saget.
-
E.
Janet Zucker
Janet Zucker is an American film producer known for her work on movies such as "Rat Race" and for her long-time collaboration and marriage with director Jerry Zucker.
- 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: Janie Blumberg Triple: [Isn't It Romantic, mainCharacter, Janie Blumberg]
Generated description
Janie Blumberg is the aspiring songwriter protagonist of the 1984 romantic comedy film "Isn't It Romantic?".
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Janie Blumberg Target entity description: Janie Blumberg is the aspiring songwriter protagonist of the 1984 romantic comedy film "Isn't It Romantic?".
-
A.
Nancy Blansky
Nancy Blansky is the central character of the 1970s American sitcom "Blansky's Beauties," portrayed as a seasoned Las Vegas showbiz professional managing a troupe of young performers.
-
B.
Jill Krementz
Jill Krementz is an American photographer and author best known for her portraits of writers and her work in children's literature.
-
C.
Marla Frumkin
Marla Frumkin is an American voice actress best known for portraying Velma Dinkley in the Scooby-Doo animated franchise.
-
D.
Sherri Kramer
Sherri Kramer is an American screenwriter and the former wife of late comedian and actor Bob Saget.
-
E.
Janet Zucker
Janet Zucker is an American film producer known for her work on movies such as "Rat Race" and for her long-time collaboration and marriage with director Jerry Zucker.
- 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e500f913d48190b41a1e37ca05e8b1 |
completed | April 19, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07ccafa04c8190849980aeda8f3435 |
completed | May 16, 2026, 1:47 a.m. |
| NEDg | Description generation | batch_6a07cfbebe848190a1e7cce64ec19df9 |
completed | May 16, 2026, 2 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07d050623c8190bfd3c05193794101 |
completed | May 16, 2026, 2:02 a.m. |
Created at: April 10, 2026, 10:35 a.m.