Triple
T12180285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Count Dracula |
E290198
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object | Bram Stoker |
E50289
|
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: Bram Stoker | Statement: [Count Dracula, creator, Bram Stoker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bram Stoker Context triple: [Count Dracula, creator, Bram Stoker]
-
A.
Bram Stoker
chosen
Bram Stoker was an Irish author best known for his 1897 novel "Dracula," a foundational work of Gothic horror fiction.
-
B.
Donald Stoker
Donald Stoker is a military historian and author known for his works on strategy, war, and international relations.
-
C.
Irving Noel Thornley Stoker
Irving Noel Thornley Stoker was the son of Irish author Bram Stoker, best known for writing the classic Gothic novel "Dracula."
-
D.
Robert B. Stoker
Robert B. Stoker is an American political scientist and public policy scholar known for his work on urban politics, social welfare policy, and governance.
-
E.
Thomas Philip Le Fanu
Thomas Philip Le Fanu was an Irish clergyman and scholar best known as the father of Victorian Gothic writer Sheridan Le Fanu.
- 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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d915fc451c819086a2a97967b82908 |
completed | April 10, 2026, 3:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f6ab19288190a882c842d74a2e30 |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:50 p.m.