Triple
T1408212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blade II |
E31744
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Luke Goss |
E111623
|
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: Luke Goss | Statement: [Blade II, starring, Luke Goss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luke Goss Context triple: [Blade II, starring, Luke Goss]
-
A.
Luke Goss
chosen
Luke Goss is an English actor and former drummer best known for his roles in genre films such as "Blade II" and "Hellboy II: The Golden Army."
-
B.
Richard Gant
Richard Gant is an American character actor known for his roles in film and television, often portraying authoritative or tough-minded figures.
-
C.
Jonathan Tucker
Jonathan Tucker is an American actor known for his intense, character-driven roles in film and television, including prominent performances in series like "Kingdom," "Westworld," and "City on a Hill."
-
D.
Michael Ealy
Michael Ealy is an American actor known for his roles in films like "Barbershop," "Think Like a Man," and "2 Fast 2 Furious," as well as various television series.
-
E.
Casper Van Dien
Casper Van Dien is an American actor best known for his leading role as Johnny Rico in the science fiction film "Starship Troopers."
- 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_69a49918e1f88190ba610f9dc8114578 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3bf7f0c8190aee96818de6ff4a5 |
completed | March 1, 2026, 10:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad36fb2c348190860129f84ca59cc3 |
completed | March 8, 2026, 8:44 a.m. |
Created at: March 1, 2026, 7:59 p.m.