Triple
T4440460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Make America Great Again |
E95757
|
entity |
| Predicate | hasOpposingMovement |
P437
|
FINISHED |
| Object | anti-Trump movement |
—
|
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: anti-Trump movement | Statement: [Make America Great Again, hasOpposingMovement, anti-Trump movement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpposingMovement Context triple: [Make America Great Again, hasOpposingMovement, anti-Trump movement]
-
A.
hasOpposingSide
Indicates that one entity possesses or is associated with another entity that lies on the opposite or facing side relative to a reference orientation or boundary.
-
B.
hasOpposingFront
Indicates that one entity’s front side is directly facing or oriented opposite to the front side of another entity.
-
C.
hasOpposingForceType
Indicates that one force is characterized as being of a type that opposes or counteracts another force.
-
D.
usesMovement
Indicates that an entity performs or involves some form of movement as part of its action or behavior.
-
E.
opposedBy
chosen
Indicates that one entity actively resists, disagrees with, or works against the actions, views, or position of another entity.
- 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_69b3453ea2b48190a26f154b3b8fece5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355ac05e081908411089c05fc36bd |
completed | March 13, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69b34f62c180819097ced38da2052207 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:32 p.m.