Triple
T21602155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Violent Ones |
E533072
|
entity |
| Predicate | hasPoliticalElements |
P109963
|
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: [The Violent Ones, hasPoliticalElements, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPoliticalElements Context triple: [The Violent Ones, hasPoliticalElements, true]
-
A.
hasPoliticalComponent
chosen
Indicates that something includes, involves, or is influenced by political factors, interests, or considerations.
-
B.
hasLegalAndPoliticalElements
Indicates that a situation, issue, or relationship involves both legal aspects (laws, regulations, rights) and political aspects (power, governance, policy decisions) at the same time.
-
C.
hasPoliticalCharacteristic
Indicates that an entity possesses a specific political attribute, quality, or affiliation.
-
D.
hasPoliticalComposition
Indicates that an entity has a particular political makeup or distribution of political affiliations, parties, or ideologies.
-
E.
hasPoliticalCurrent
Indicates that an entity is associated with, aligned to, or characterized by a particular political current, ideology, or movement.
- 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_69e0c46364608190a337dc8720dc2a35 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef17e247588190a57f27ba04f4f21a |
completed | April 27, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69e69665fe8c8190af7e38785db188b2 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:33 p.m.