Triple
T25463060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamazgha |
E638101
|
entity |
| Predicate | opposedToTerm |
P126719
|
FINISHED |
| Object | exclusive Arabization of North Africa |
—
|
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: exclusive Arabization of North Africa | Statement: [Tamazgha, opposedToTerm, exclusive Arabization of North Africa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opposedToTerm Context triple: [Tamazgha, opposedToTerm, exclusive Arabization of North Africa]
-
A.
opposedNumberOfTerms
Indicates that two entities are in opposition with respect to the number of terms they involve or are associated with.
-
B.
opposedBy
Indicates that one entity actively resists, disagrees with, or works against the actions, views, or position of another entity.
-
C.
opposesPhrase
chosen
Indicates that one entity expresses disagreement with, resistance to, or argument against the idea, statement, or position represented by the phrase.
-
D.
opposedQualityTo
Indicates that one quality stands in direct opposition or contrast to another quality.
-
E.
theoryOpposed
Indicates that one theory stands in opposition to, or conflicts with, another theory.
- 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_69e75db8bab08190baca80b4a8c315fd |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f627aedf548190bc9f53c8a2d67b50 |
completed | May 2, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69f623a4e1048190bbb8dd1253fdcee9 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 21, 2026, 2:13 p.m.