Triple
T32637525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dewey Crowe |
E834386
|
entity |
| Predicate | recurringOppositionTo |
P437
|
FINISHED |
| Object | protagonists of Justified |
—
|
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: protagonists of Justified | Statement: [Dewey Crowe, recurringOppositionTo, protagonists of Justified]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recurringOppositionTo Context triple: [Dewey Crowe, recurringOppositionTo, protagonists of Justified]
-
A.
opposedBy
chosen
Indicates that one entity actively resists, disagrees with, or works against the actions, views, or position of another entity.
-
B.
typeOfOpposition
Indicates a relationship where one entity stands in opposition or contrast to another, such as being a rival, adversary, or countering force.
-
C.
emergedInOppositionTo
Indicates that one entity came into existence or gained prominence specifically as a reaction or counter-movement against another entity.
-
D.
theoryOpposed
Indicates that one theory stands in opposition to, or conflicts with, another theory.
-
E.
hasOppositionalElements
Indicates that something contains components or aspects that are in conflict, contrast, or opposition to each other.
- 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_69f3492dc2308190a88c6e30a3f3f576 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6cd126fcc8190aa1f1f146e45ec0c |
completed | May 3, 2026, 4:20 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1470808190b70cdfd7a6395670 |
completed | May 3, 2026, 4:16 a.m. |
Created at: May 1, 2026, 1:07 a.m.