Triple
T21384398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Schink |
E527452
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Legion (2010 film) |
—
|
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: Legion (2010 film) | Statement: [Peter Schink, notableWork, Legion (2010 film)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Legion (2010 film) Context triple: [Peter Schink, notableWork, Legion (2010 film)]
-
A.
Legion (2010 film)
chosen
Legion is a 2010 apocalyptic supernatural action-horror film in which the archangel Michael defies God to protect humanity from a legion of possessed angels.
-
B.
Legion
Legion is Lenovo's gaming-focused brand of high-performance laptops, desktops, and related PC hardware.
-
C.
Legion
"Legion" is a bonus track associated with the influential Swedish melodic death metal band At the Gates, known for its aggressive style and dark, intense atmosphere.
-
D.
Legion
Legion is a powerful antagonistic force or organization that serves as the primary enemy opposed by Grace Harper.
-
E.
Legion
Legion is a psychological horror television series that blends superhero elements with surreal storytelling, centered on a troubled man who may be the most powerful mutant alive.
- 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_69e0b51f363c8190944000ab5523b02b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b0f211c08190b3a129eaa725422e |
completed | April 22, 2026, 11:28 a.m. |
Created at: April 16, 2026, 5:12 p.m.