Triple
T16754666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Our Lord of Esquipulas |
E407177
|
entity |
| Predicate | hasMiracleTradition |
P73224
|
FINISHED |
| Object | healing illnesses |
—
|
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: healing illnesses | Statement: [Our Lord of Esquipulas, hasMiracleTradition, healing illnesses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMiracleTradition Context triple: [Our Lord of Esquipulas, hasMiracleTradition, healing illnesses]
-
A.
miracleTradition
chosen
Indicates that a miracle is associated with, preserved in, or transmitted through a particular religious or cultural tradition.
-
B.
hasMiracleScene
Indicates that a scene involves a miraculous or supernatural event occurring.
-
C.
miracleType
Indicates the specific category or kind of miracle associated with an event or entity.
-
D.
numberOfMiraclesTraditionallyAssociated
Indicates the traditionally recognized count of miracles that are associated with a particular entity or subject.
-
E.
associatedWithMiracle
Indicates a relationship in which something is connected to, involved in, or characterized by a miracle.
- 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_69d8839174188190909f190097207065 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3abe6b68c8190a5e2a11973f01b8e |
completed | April 18, 2026, 4:05 p.m. |
| PD | Predicate disambiguation | batch_69e319cbd79c8190a03587a61c18bec0 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:21 a.m.