Triple
T3820084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Spy Who Dumped Me |
E84350
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Susanna Fogel |
E450471
|
NE FINISHED |
How this triple was built (2 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: Susanna Fogel | Statement: [The Spy Who Dumped Me, screenwriter, Susanna Fogel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Susanna Fogel Context triple: [The Spy Who Dumped Me, screenwriter, Susanna Fogel]
-
A.
Susanna Fogel
chosen
Susanna Fogel is an American filmmaker and screenwriter known for directing sharp, character-driven comedies and dramedies, often centered on complex female friendships and offbeat humor.
-
B.
Carol Mendelsohn
Carol Mendelsohn is an American television producer and writer best known for her influential work shaping the CSI franchise and modern crime procedural dramas.
-
C.
Claudia Finkelstein
Claudia Finkelstein is a physician and academic known for her work in internal medicine and physician well-being.
-
D.
Juliana Minsky
Juliana Minsky is a daughter of pioneering artificial intelligence researcher Marvin Minsky.
-
E.
Susan Friedlander
Susan Friedlander is an American mathematician known for her contributions to fluid dynamics and partial differential equations, as well as for her leadership roles in the mathematical community.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69aed931f5908190be2c07af66d4df25 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeea601d408190b09dc486e77488d4 |
completed | March 9, 2026, 3:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdc51a7c6081909eeda563a4485e87 |
completed | March 20, 2026, 10:07 p.m. |
Created at: March 9, 2026, 3:17 p.m.