Triple
T25175737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess Leonore d’Este |
E630440
|
entity |
| Predicate | relationshipToTorquatoTasso |
P178743
|
FINISHED |
| Object | patron-like figure |
—
|
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: patron-like figure | Statement: [Princess Leonore d’Este, relationshipToTorquatoTasso, patron-like figure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToTorquatoTasso Context triple: [Princess Leonore d’Este, relationshipToTorquatoTasso, patron-like figure]
-
A.
relationshipToDante
Indicates the specific familial, social, or other relational connection that one entity has to Dante.
-
B.
relationshipToAntonioVillalta
Indicates the nature of the relationship or connection that an entity has to Antonio Villalta.
-
C.
relationshipToFlorentinoAriza
Indicates the nature of the relationship an entity has with Florentino Ariza.
-
D.
relationshipToGustav von Aschenbach
Indicates the specific type of personal, social, or emotional connection an entity has to Gustav von Aschenbach.
-
E.
relationshipToLucentio
Indicates the specific type of relationship or connection that an entity has to Lucentio.
- 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_69e75a88fdf081908e47ae6e195c14e1 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f71422adac8190a5ceb32dcf820833 |
completed | May 3, 2026, 9:23 a.m. |
| PD | Predicate disambiguation | batch_69f712764d2c819081b64b27e5de4a13 |
completed | May 3, 2026, 9:16 a.m. |
| PDg | Predicate description generation | batch_69f71421e8d08190807ccfb15d0f0ddb |
completed | May 3, 2026, 9:23 a.m. |
Created at: April 21, 2026, 12:34 p.m.