Triple
T22741526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cattedrale di Sant’Agata |
E562425
|
entity |
| Predicate | majorReconstructionCause |
P149546
|
FINISHED |
| Object | 1693 Sicily earthquake |
—
|
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: 1693 Sicily earthquake | Statement: [Cattedrale di Sant’Agata, majorReconstructionCause, 1693 Sicily earthquake]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorReconstructionCause Context triple: [Cattedrale di Sant’Agata, majorReconstructionCause, 1693 Sicily earthquake]
-
A.
causeOfDisaster
Indicates that the subject is responsible for bringing about or triggering the specified disaster.
-
B.
hasMajorReconstruction
Indicates that an entity has undergone a significant or extensive reconstruction or renovation.
-
C.
majorConstruction
Indicates a relationship where a construction project is large-scale, significant, or of primary importance in scope, impact, or resources.
-
D.
disasterCauseDetail
Indicates a detailed explanation of the specific cause or contributing factors behind a disaster.
-
E.
reconstructionWork
Indicates that an entity is engaged in or associated with activities to rebuild, restore, or repair something that was damaged, destroyed, or altered.
- 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_69e245513a5c81908d5cb471b4fc429d |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1797400fc8190bec26726f434f787 |
completed | April 29, 2026, 3:22 a.m. |
| PD | Predicate disambiguation | batch_69eed2a971c0819088af574e40c9343f |
completed | April 27, 2026, 3:06 a.m. |
| PDg | Predicate description generation | batch_69eeeb5681f88190821129ced752f190 |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 17, 2026, 3:23 p.m.