Triple
T6208592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tommy Ross |
E138809
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Carrie White |
E119773
|
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: Carrie White | Statement: [Tommy Ross, associatedWith, Carrie White]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carrie White Context triple: [Tommy Ross, associatedWith, Carrie White]
-
A.
Carrie White
chosen
Carrie White is the telekinetic, tormented teenage girl at the center of Stephen King’s horror novel "Carrie," whose abuse and humiliation lead to a catastrophic act of revenge.
-
B.
Carrie Rawlins
Carrie Rawlins is a young orphaned girl and one of the main child characters in the Disney film "Bedknobs and Broomsticks."
-
C.
Tracy Voorhees
Tracy Voorhees was a mid-20th-century American lawyer and government official who played key administrative roles in the U.S. military establishment, particularly during and after World War II.
-
D.
Charlotte Stant
Charlotte Stant is a central figure in Henry James's novel "The Golden Bowl," known for her complex emotional entanglements and morally ambiguous role in the story's intricate web of relationships.
-
E.
Gretchen Krueger
Gretchen Krueger is a researcher and author known for her work on CLIP, a multimodal AI model that connects images and text.
- 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_69c008ada364819096c9e92c74d639b5 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062870d5881909b8d4e33ff31a907 |
completed | March 22, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c16f52829c81909bdd422cbb1eabf4 |
completed | March 23, 2026, 4:50 p.m. |
Created at: March 22, 2026, 4:21 p.m.