Triple
T5776017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bride of Frankenstein |
E127442
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Boris Karloff |
E218089
|
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: Boris Karloff | Statement: [Bride of Frankenstein, stars, Boris Karloff]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boris Karloff Context triple: [Bride of Frankenstein, stars, Boris Karloff]
-
A.
Boris Karloff
chosen
Boris Karloff was an English actor best known for his iconic portrayals in classic horror films, particularly as Frankenstein's monster in the 1931 film "Frankenstein."
-
B.
Bela Lugosi
Bela Lugosi was a Hungarian-American actor best known for his iconic portrayal of Count Dracula in early horror cinema.
-
C.
Vincent Price
Vincent Price was an American actor renowned for his distinctive voice and charismatic presence, particularly in classic horror films and gothic dramas.
-
D.
Vincent E. Price
Vincent E. Price is an American political communication scholar and academic leader who serves as the president of Duke University.
-
E.
Peter Cushing
Peter Cushing was an English actor best known for his roles in classic Hammer horror films and as Grand Moff Tarkin in Star Wars.
- 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_69c008361fa88190aefa4dc41b051e7f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029de3bb4819087a6f3e920e12990 |
completed | March 22, 2026, 5:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0980d833481908e69a80a63bbe256 |
completed | March 23, 2026, 1:31 a.m. |
Created at: March 22, 2026, 3:50 p.m.