Triple
T35014069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mouse |
E1010006
|
entity |
| Predicate | isOftenOpposedTo |
P35001
|
FINISHED |
| Object | Cat |
—
|
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: Cat | Statement: [Mouse, isOftenOpposedTo, Cat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOftenOpposedTo Context triple: [Mouse, isOftenOpposedTo, Cat]
-
A.
typeOfOpposition
chosen
Indicates a relationship where one entity stands in opposition or contrast to another, such as being a rival, adversary, or countering force.
-
B.
opposedBy
Indicates that one entity actively resists, disagrees with, or works against the actions, views, or position of another entity.
-
C.
theoryOpposed
Indicates that one theory stands in opposition to, or conflicts with, another theory.
-
D.
isOppositionCounterpartOf
Indicates a relationship where one entity serves as the opposing or counterpart force, side, or position to another within a conflict, competition, or contrast.
-
E.
opposedQualityTo
Indicates that one quality stands in direct opposition or contrast to another quality.
- 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_69f76dcc3ac8819096a3ed52f5fa2523 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7858aa5508190a07dde993b3356fc |
completed | May 3, 2026, 5:27 p.m. |
| PD | Predicate disambiguation | batch_69f7841812f081909d878955d114088e |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4:01 p.m.