Triple
T19481595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Count Vertigo |
E487397
|
entity |
| Predicate | realName |
P9233
|
FINISHED |
| Object | Werner Vertigo |
—
|
NE NERFINISHED |
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: Werner Vertigo | Statement: [Count Vertigo, realName, Werner Vertigo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Werner Vertigo Context triple: [Count Vertigo, realName, Werner Vertigo]
-
A.
Mr. Vertigo
Mr. Vertigo is a novel by Paul Auster that blends magical realism and coming-of-age themes in the story of a boy who learns to levitate under the tutelage of a mysterious master in early 20th-century America.
-
B.
Count Vertigo
chosen
Count Vertigo is a DC Comics supervillain, primarily an enemy of Green Arrow, known for his aristocratic background and powers that disrupt his opponents’ balance and perception.
-
C.
Vértigo
Vértigo is a popular Chilean television talk and entertainment show known for its celebrity interviews, comedy segments, and live audience interaction.
-
D.
Vértigo
Vértigo is a roller coaster attraction located at Parque de Atracciones de Madrid in Spain.
-
E.
Invertigo
Invertigo is a shuttle-style inverted roller coaster model designed by Vekoma, featuring face-to-face seating and multiple inversions ridden both forwards and backwards.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d924388190b847cb15bb3d0aff |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e634393b8081909f5e4c38b2f1a9b7 |
completed | April 20, 2026, 2:12 p.m. |
Created at: April 10, 2026, 1:39 p.m.