Triple
T29534690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blown Away (1994 film) |
E749303
|
entity |
| Predicate | hasExplosivesExpertAntagonist |
P178310
|
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: [Blown Away (1994 film), hasExplosivesExpertAntagonist, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExplosivesExpertAntagonist Context triple: [Blown Away (1994 film), hasExplosivesExpertAntagonist, true]
-
A.
explosiveClass
Indicates the classification or category assigned to an explosive based on its type, properties, or regulatory class.
-
B.
hasTerroristAntagonist
Indicates that the subject work features an antagonist who is a terrorist or engages in terrorism.
-
C.
explosiveDevice
Indicates the presence or involvement of an object designed to explode or cause an explosion in relation to the associated entities.
-
D.
explosiveMaterialUsed
Indicates that an explosive material was employed or involved in carrying out a particular action or event.
-
E.
explosiveComponents
Indicates that one entity consists of, contains, or is associated with components that are explosive or used to create an explosive device.
- 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_69f0bd47abb081909bd6e6a33d770fd8 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f70e8755a48190931eaa77946f9460 |
completed | May 3, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f70abc00848190a1c3f495ef6c8dc6 |
completed | May 3, 2026, 8:43 a.m. |
| PDg | Predicate description generation | batch_69f70e854b9c8190a3416e2189e17742 |
completed | May 3, 2026, 8:59 a.m. |
Created at: April 28, 2026, 4:56 p.m.