Triple
T28779916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reginald De Courcy |
E726646
|
entity |
| Predicate | isCharmedBy |
P165582
|
FINISHED |
| Object | Lady Susan Vernon |
—
|
NE NERFINISHED |
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: Lady Susan Vernon | Statement: [Reginald De Courcy, isCharmedBy, Lady Susan Vernon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCharmedBy Context triple: [Reginald De Courcy, isCharmedBy, Lady Susan Vernon]
-
A.
hasCharm
Indicates that an entity possesses or exhibits charm, attractiveness, or an appealing quality.
-
B.
enchantedBy
Indicates that one entity has cast or holds a magical enchantment over another entity.
-
C.
enchantedAs
Indicates that one entity has been placed under a magical spell or charm by another entity or force.
-
D.
enchantedTo
Indicates that one entity has been magically imbued or altered so that it possesses a special effect, property, or behavior caused by another entity.
-
E.
isBelovedOf
Indicates that one entity is deeply loved, cherished, or held in special affection by another entity.
- F. None of above. chosen
Provenance (4 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_69f03199997c8190b6ae43fb19312443 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f6596b210481908af6cd555748f75b |
completed | May 2, 2026, 8:07 p.m. |
| PD | Predicate disambiguation | batch_69f65760fd3081908ffe014a5e2bf069 |
completed | May 2, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f658ebeca4819096beb3f98f73fe31 |
completed | May 2, 2026, 8:05 p.m. |
Created at: April 28, 2026, 6:19 a.m.