Triple
T17538973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | square of opposition |
E427132
|
entity |
| Predicate | subcontraryPairs |
P69696
|
FINISHED |
| Object | I and O |
—
|
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: I and O | Statement: [square of opposition, subcontraryPairs, I and O]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subcontraryPairs Context triple: [square of opposition, subcontraryPairs, I and O]
-
A.
counterpartRelation
Indicates a reciprocal relationship where two entities serve as corresponding or equivalent counterparts to each other in a given context.
-
B.
hasConceptualOpposite
Indicates that one entity represents a concept that is fundamentally opposed or contrary in meaning to the concept represented by another entity.
-
C.
commonPair
chosen
Indicates that two entities commonly occur together or are frequently associated as a pair in some shared context.
-
D.
typeOfOpposition
Indicates a relationship where one entity stands in opposition or contrast to another, such as being a rival, adversary, or countering force.
-
E.
opposedBy
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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4536ec5f48190acff6671712d40c7 |
completed | April 19, 2026, 4 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f8b9888190aa8a45e09acf4319 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:49 a.m.