Triple
T5425665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | E(n) |
E121355
|
entity |
| Predicate | hasInverseOperation |
P21517
|
FINISHED |
| Object | inverse isometry |
—
|
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: inverse isometry | Statement: [E(n), hasInverseOperation, inverse isometry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInverseOperation Context triple: [E(n), hasInverseOperation, inverse isometry]
-
A.
hasReverse
Indicates that one entity serves as the inverse or opposite counterpart of another entity in a given relationship or operation.
-
B.
isInverseOf
chosen
Indicates that one relation reverses the direction of another, so that if the original relates A to B, its inverse relates B to A.
-
C.
hasInversionCapability
Indicates that an entity possesses the ability to reverse or invert another entity, state, or process.
-
D.
opposedOperation
Indicates that one operation is in conflict with, counters, or works against another operation.
-
E.
hasOppositeNumberForm
Indicates that one entity is represented by a number form that is the opposite (e.g., additive vs. subtractive, positive vs. negative, or otherwise contrastive) of the number form used to represent the other 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_69bd463b58d88190b258261573de9e91 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8911a7348190ad9378a248190f07 |
completed | March 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69bd846b8bdc81909dcdc2a3084226f2 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:06 p.m.