Triple
T2351846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penny Dreadful |
E47464
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Dracula |
E48891
|
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: Dracula | Statement: [Penny Dreadful, featuresCharacter, Dracula]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dracula Context triple: [Penny Dreadful, featuresCharacter, Dracula]
-
A.
Dracula
chosen
Dracula is Bram Stoker’s 1897 Gothic horror novel that introduced the iconic vampire Count Dracula and helped define modern vampire fiction.
-
B.
Horror of Dracula
Horror of Dracula is a 1958 British gothic horror film from Hammer Film Productions, renowned for its vivid color, atmospheric style, and Christopher Lee’s iconic portrayal of Count Dracula.
-
C.
The Vampire
"The Vampire" is a film featuring actress Lydia Reed, known for her work in mid-20th-century American cinema.
-
D.
Vampire
"Vampire" is a famous 1895 painting by Norwegian artist Edvard Munch, depicting a woman with flowing red hair bending over a man's neck in a dark, intimate embrace.
-
E.
Vampirina
Vampirina is an animated Disney Junior television series that follows a young vampire girl adjusting to life in the human world after moving from Transylvania to Pennsylvania.
- 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_69a88a1b678c8190bce986922ba60ce0 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc6f8ff548190b07505310e2bf0b9 |
completed | March 7, 2026, 6:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae9631c9a481909a3051ac06afdca7 |
completed | March 9, 2026, 9:43 a.m. |
Created at: March 4, 2026, 7:54 p.m.