Triple
T34774136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Repartition |
E1002453
|
entity |
| Predicate | opposedMethod |
P107791
|
FINISHED |
| Object | individual terrorism |
—
|
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: individual terrorism | Statement: [Black Repartition, opposedMethod, individual terrorism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opposedMethod Context triple: [Black Repartition, opposedMethod, individual terrorism]
-
A.
opposedApproach
chosen
Indicates that one entity actively disagrees with, resists, or works against the method, strategy, or course of action proposed or taken by another entity.
-
B.
opposedBy
Indicates that one entity actively resists, disagrees with, or works against the actions, views, or position of another entity.
-
C.
opposedOperation
Indicates that one operation is in conflict with, counters, or works against another operation.
-
D.
theoryOpposed
Indicates that one theory stands in opposition to, or conflicts with, another theory.
-
E.
opposesClass
Indicates a relationship where one entity actively resists, challenges, or works against the interests, actions, or status of a particular social or economic class.
- 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_69f76db30a108190bb57ca95b873e5bb |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fd3a69f1e08190a11aed015bff0858 |
completed | May 8, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69fd39124180819080ca7911d3515d6d |
completed | May 8, 2026, 1:14 a.m. |
Created at: May 3, 2026, 3:59 p.m.