Triple
T9854122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Material Girls |
E239541
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Gina Wendkos |
E661919
|
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: Gina Wendkos | Statement: [Material Girls, screenwriter, Gina Wendkos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gina Wendkos Context triple: [Material Girls, screenwriter, Gina Wendkos]
-
A.
Gina Wendkos
chosen
Gina Wendkos is an American screenwriter best known for adapting Meg Cabot’s novel into the hit teen film "The Princess Diaries" and writing several other popular romantic comedies.
-
B.
Gina Schock
Gina Schock is an American drummer best known as the powerhouse behind the pioneering all-female rock band The Go-Go’s.
-
C.
Gina Cirone
Gina Cirone is an American woman best known as the wife of actor William Petersen, star of the television series "CSI: Crime Scene Investigation."
-
D.
Gina Barrisano
Gina Barrisano is a central character in the film "Beautiful Girls," portrayed as a charismatic and emotionally complex young woman navigating relationships and small-town life.
-
E.
Gina Girolamo
Gina Girolamo is a television producer best known for her executive production work on the post-apocalyptic drama series "The 100."
- 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_69ca84e4fdc08190a624425bcef98665 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb376d32c819089381cf6ed83629d |
completed | April 2, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e23aeb6f9c8190a986af35bcf353f7 |
completed | April 17, 2026, 1:51 p.m. |
Created at: March 30, 2026, 8:34 p.m.