Triple
T17025918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Vampire |
E413062
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | Mr. Vampire |
E413062
|
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: Mr. Vampire | Statement: [Mr. Vampire, title, Mr. Vampire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Vampire Context triple: [Mr. Vampire, title, Mr. Vampire]
-
A.
Mr. Vampire
chosen
Mr. Vampire is a classic 1985 Hong Kong horror-comedy film that popularized the hopping vampire (jiangshi) genre and became a landmark of Chinese supernatural cinema.
-
B.
Vampiro
Vampiro is a Canadian professional wrestler and commentator known for his dark, gothic persona and influential roles in Mexican and American lucha libre promotions.
-
C.
The Vampire
"The Vampire" is a film featuring actress Lydia Reed, known for her work in mid-20th-century American cinema.
-
D.
The Vampire
The Vampire is a famous 1897 painting by Philip Burne-Jones depicting a seductive female vampire looming over a male victim, often associated with themes of fatal attraction and the femme fatale.
-
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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d5d46a5081908bc5681621dd8534 |
completed | April 18, 2026, 7:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012334c3b48190b125ab926450c45b |
completed | May 11, 2026, 12:30 a.m. |
Created at: April 10, 2026, 5:33 a.m.