Triple
T12326553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Il trittico |
E293843
|
entity |
| Predicate | settingOfSuorAngelica |
P12690
|
FINISHED |
| Object | convent near Siena |
—
|
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: convent near Siena | Statement: [Il trittico, settingOfSuorAngelica, convent near Siena]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfSuorAngelica Context triple: [Il trittico, settingOfSuorAngelica, convent near Siena]
-
A.
featuresAngel
Indicates that something includes or prominently presents an angel as a central element or subject.
-
B.
settingOfMyth
Indicates that a location or environment serves as the backdrop or context in which a particular myth takes place.
-
C.
commandedByAngelTo
Indicates that an entity is instructed or directed to perform an action or adopt a state as a result of a command given by an angel.
-
D.
settingOfTemptation
Indicates the location or context in which a temptation occurs or is experienced.
-
E.
theatricalSetting
chosen
Indicates the spatial or contextual environment in which a theatrical performance or dramatic action takes place.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ec5be788190b82d2edc6a0f1095 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.