Triple
T9801874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Bloody Valentine |
E237857
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Debra Karen |
E380553
|
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: Debra Karen | Statement: [My Bloody Valentine, editedBy, Debra Karen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Debra Karen Context triple: [My Bloody Valentine, editedBy, Debra Karen]
-
A.
Debra Karen
chosen
Debra Karen is a film editor best known for her work on the comedy movie "Meatballs."
-
B.
Debra
Debra is a central character in Cory Doctorow's science fiction novel "Down and Out in the Magic Kingdom," set in a futuristic, reputation-based society at Disney World.
-
C.
Debra
Debra is a feminine given name commonly used in English-speaking countries, derived from the Hebrew name Deborah meaning "bee."
-
D.
Debra Lynn
Debra Lynn is best known as the wife of Ian Murdock, the founder of the Debian operating system.
-
E.
Debra Hayward
Debra Hayward is a British film producer known for her work on major feature films, including the acclaimed musical adaptation "Les Misérables" (2012).
- 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_69ca84dd4608819097ff4ed00feca280 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda62b41048190bcef70a7591830c6 |
completed | April 1, 2026, 11:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1c44edac48190a44fdfb858d0dbba |
completed | April 5, 2026, 2:09 a.m. |
Created at: March 30, 2026, 8:29 p.m.