Triple
T12043046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jigsaw |
E286710
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | John Kramer |
E932993
|
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: John Kramer | Statement: [Jigsaw, featuresCharacter, John Kramer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Kramer Context triple: [Jigsaw, featuresCharacter, John Kramer]
-
A.
John Kramer
chosen
John Kramer is the fictional serial killer known as "Jigsaw," the central antagonist of the Saw horror film franchise.
-
B.
Benjamin Poindexter
Benjamin Poindexter is a Marvel Comics supervillain better known as Bullseye, an expert marksman and deadly assassin often depicted as an enemy of Daredevil.
-
C.
Aldrich Killian
Aldrich Killian is the primary antagonist in Marvel's Iron Man 3, a brilliant but vengeful scientist who develops the Extremis virus to gain superhuman abilities and challenge Tony Stark.
-
D.
John Keen
John Keen is a notable individual distinguished enough to be specifically recognized as a prominent bearer of the surname Keen.
-
E.
Robert Barrat
Robert Barrat was an American character actor known for his supporting roles in numerous Hollywood films from the 1930s through the 1950s.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9040d13108190bd1a969fa62aae5a |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f649dbf081908e76c45e362217c1 |
completed | May 2, 2026, 1:04 p.m. |
Created at: April 8, 2026, 9:47 p.m.