Triple
T38599598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Alfonso |
E934171
|
entity |
| Predicate | associatedWithAria |
P8272
|
FINISHED |
| Object | “È la fede delle femmine” |
E1483335
|
NE 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: “È la fede delle femmine” | Statement: [Don Alfonso, associatedWithAria, “È la fede delle femmine”]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithAria Context triple: [Don Alfonso, associatedWithAria, “È la fede delle femmine”]
-
A.
associatedWithAttribute
Indicates that one entity is linked to, characterized by, or described through a particular attribute.
-
B.
associatedWithElement
Indicates a relationship where one entity is linked or connected to a particular element, such that the element is relevant to, involved in, or characteristic of that entity.
-
C.
associatedWithText
chosen
Indicates that an entity has a contextual or semantic connection to a specific piece of text.
-
D.
associatedWithAccelerator
Indicates that an entity has a relationship or connection with an accelerator, such as being part of, supported by, or working in conjunction with it.
-
E.
associatedWithLabel
Indicates that an entity is connected or related to a particular label or tag used to categorize or identify it.
- F. None of above.
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_69f76ecc17688190b389b693a5927501 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41eaa61cb48190b8e72d3db9cb32ad |
completed | June 29, 2026, 3:46 a.m. |
| PD | Predicate disambiguation | batch_6a037a2026248190b894436a578d79ac |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:32 p.m.