Triple
T7499415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Die Hard with a Vengeance |
E177219
|
entity |
| Predicate | hasTerroristAntagonist |
P77872
|
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: [Die Hard with a Vengeance, hasTerroristAntagonist, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTerroristAntagonist Context triple: [Die Hard with a Vengeance, hasTerroristAntagonist, true]
-
A.
hasAntagonisticProtagonist
Indicates that the work features a main character who opposes or undermines the typical heroic or moral expectations of a traditional protagonist.
-
B.
classifiedAsTerroristBy
Indicates that an entity has been designated or labeled as a terrorist by a specified authority, organization, or actor.
-
C.
hasAntagonistGroup
Indicates that an entity is opposed or challenged by a specific group acting as its antagonist.
-
D.
hasVillain
Indicates that one entity is the villain or primary antagonist associated with another entity.
-
E.
antagonistOf
Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
- F. None of above. chosen
Provenance (4 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_69c69f2696688190915a8458f2398211 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f81b431481908214b69c6c8d83bc |
completed | March 27, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d266d88190982cf5d2ee2e9564 |
completed | March 27, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69c6f8184bb08190b2f70545a6aa277c |
completed | March 27, 2026, 9:35 p.m. |
Created at: March 27, 2026, 3:44 p.m.