Triple
T28656144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Every Which Way film series |
E725335
|
entity |
| Predicate | recurringAntagonistGroup |
P17627
|
FINISHED |
| Object | Black Widows motorcycle gang |
—
|
NE NERFINISHED |
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: Black Widows motorcycle gang | Statement: [Every Which Way film series, recurringAntagonistGroup, Black Widows motorcycle gang]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recurringAntagonistGroup Context triple: [Every Which Way film series, recurringAntagonistGroup, Black Widows motorcycle gang]
-
A.
hasAntagonistGroup
chosen
Indicates that an entity is opposed or challenged by a specific group acting as its antagonist.
-
B.
villainOrganization
Indicates that an entity is an organization characterized as antagonistic, criminal, or evil within a given context or narrative.
-
C.
primaryAntagonists
Indicates that the referenced entities serve as the main opposing or adversarial forces in relation to a specified subject or narrative.
-
D.
antagonistOf
Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
-
E.
laterEnemyOf
Indicates that one entity becomes an enemy of another at a later time, after not initially being in an antagonistic relationship.
- 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_69f01d84f5f0819087ab5e6143b14ed7 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f658ee40088190b71e1219407690d0 |
completed | May 2, 2026, 8:05 p.m. |
| PD | Predicate disambiguation | batch_69f65760fd3081908ffe014a5e2bf069 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 4:55 a.m.