Triple
T10394482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Snowman (2017 film) |
E244974
|
entity |
| Predicate | hasSerialKillerAntagonist |
P63359
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [The Snowman (2017 film), hasSerialKillerAntagonist, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSerialKillerAntagonist Context triple: [The Snowman (2017 film), hasSerialKillerAntagonist, true]
-
A.
hasSerialKiller
chosen
Indicates that one entity is a serial killer associated with, responsible for, or targeting another entity.
-
B.
hasTerroristAntagonist
Indicates that the subject work features an antagonist who is a terrorist or engages in terrorism.
-
C.
hasAntagonisticProtagonist
Indicates that the work features a main character who opposes or undermines the typical heroic or moral expectations of a traditional protagonist.
-
D.
hasVillain
Indicates that one entity is the villain or primary antagonist associated with another entity.
-
E.
perpetratorOfKilling
Indicates that an entity is the one who carried out or caused a particular killing.
- F. None of above.
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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9b795fc8190aa50ce3c7360ff83 |
completed | April 7, 2026, 11:25 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb438c481908dff87c47de2f069 |
completed | April 7, 2026, 10:43 a.m. |
Created at: April 6, 2026, 12:06 p.m.