Triple
T26341855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irene Cassini |
E662666
|
entity |
| Predicate | hasImperfection |
P95465
|
FINISHED |
| Object | not genetically perfect |
—
|
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: not genetically perfect | Statement: [Irene Cassini, hasImperfection, not genetically perfect]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasImperfection Context triple: [Irene Cassini, hasImperfection, not genetically perfect]
-
A.
hasIssueWith
Indicates that one entity experiences a problem, conflict, or concern related to another entity.
-
B.
hasAberrationCharacteristics
Indicates that an entity exhibits traits or properties that deviate from what is considered normal, standard, or expected.
-
C.
defect
chosen
Indicates that an entity has a fault, imperfection, or malfunction that causes it to deviate from an expected standard or proper functioning.
-
D.
hasScar
Indicates that one entity bears or possesses a scar on its body.
-
E.
defectsFrom
Indicates a relationship where an entity abandons, deserts, or switches allegiance away from another entity, often to join an opposing side.
- 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_69ee81304194819092e20e0fae3aee07 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f65aa07c048190a5df30d53d8f0cf5 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 26, 2026, 10:39 p.m.