Triple
T30825453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Deadly Attachment |
E785049
|
entity |
| Predicate | featuresAntagonistNationality |
P201892
|
FINISHED |
| Object | German |
—
|
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: German | Statement: [The Deadly Attachment, featuresAntagonistNationality, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresAntagonistNationality Context triple: [The Deadly Attachment, featuresAntagonistNationality, German]
-
A.
featuresAntagonistEntity
Indicates that the subject includes or involves an entity serving as an antagonist in the context of a narrative, interaction, or scenario.
-
B.
antagonistOrigin
Indicates the source, background, or cause from which an antagonist or opposing force arises in relation to another entity or narrative.
-
C.
antagonistAlterEgoOf
Indicates that one entity serves as the primary opposing force or enemy of another entity’s alternate identity or secret persona.
-
D.
antagonistBaseOf
Indicates that one entity serves as the primary base, headquarters, or stronghold from which an antagonist operates or exerts influence over another entity.
-
E.
antagonistOccupation
Indicates the role, job, or professional activity that the antagonist character performs.
- 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_69f224b6642481909e8d701de2cd1a53 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a002f0839fc8190a874d3b0d0826d7e |
completed | May 10, 2026, 7:08 a.m. |
| PD | Predicate disambiguation | batch_6a002eae7b6481909974b321e2789b7e |
completed | May 10, 2026, 7:07 a.m. |
| PDg | Predicate description generation | batch_6a002f071de88190b1fa4f5531a6cea7 |
completed | May 10, 2026, 7:08 a.m. |
Created at: April 29, 2026, 8:44 p.m.