Triple
T19970635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Left Pillar |
E480061
|
entity |
| Predicate | hasOppositeQualityTo |
P11522
|
FINISHED |
| Object | mercy of the Right Pillar |
—
|
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: mercy of the Right Pillar | Statement: [Left Pillar, hasOppositeQualityTo, mercy of the Right Pillar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOppositeQualityTo Context triple: [Left Pillar, hasOppositeQualityTo, mercy of the Right Pillar]
-
A.
opposedQualityTo
chosen
Indicates that one quality stands in direct opposition or contrast to another quality.
-
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.
hasOppositeStatus
Indicates that two entities hold directly contrasting or mutually exclusive statuses within a given context.
-
D.
hasOppositeStructure
Indicates that one entity possesses a structure that is the inverse or opposite in form, arrangement, or organization relative to another entity.
-
E.
hasOppositeDirectionTo
Indicates that one entity’s direction is exactly reversed or opposed to the direction 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65bc89b508190879d29bef546aac8 |
completed | April 20, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69e537f7e4848190b431a69ec3f1b609 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:54 p.m.