Triple
T7907949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Millar |
E183623
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Old Man Logan |
E508704
|
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: Old Man Logan | Statement: [Mark Millar, notableWork, Old Man Logan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Old Man Logan Context triple: [Mark Millar, notableWork, Old Man Logan]
-
A.
Old Man Logan
chosen
Old Man Logan is a popular Marvel Comics storyline set in a dystopian future where an aged Wolverine navigates a villain-ruled world after the fall of the superheroes.
-
B.
The Wolverine
The Wolverine is a 2013 superhero film centered on the Marvel Comics character Wolverine, following his journey to Japan where he confronts both his past and powerful new enemies.
-
C.
LOGAN
LOGAN is the radio callsign used by Loganair, a Scottish regional airline operating domestic and short-haul international flights.
-
D.
Legion
"Legion" is a 2010 supernatural action-horror film in which archangel Michael defies God to protect humanity from an impending apocalypse.
-
E.
Legion
Legion is a powerful extraterrestrial kaiju from the Gamera film series, known for its insect-like appearance and role as one of Gamera’s most formidable adversaries.
- 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_69ca828dec0c81908b8f55a4dbbb53ff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a59de00819099f1ce02bb469e75 |
completed | March 31, 2026, 3:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5bd0024c81909679a45612bcb1a7 |
completed | March 31, 2026, 5:29 a.m. |
Created at: March 30, 2026, 5:03 p.m.