Triple
T25682611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Novena to Our Lady of Lourdes |
E643980
|
entity |
| Predicate | commonIntention |
P75772
|
FINISHED |
| Object | healing |
—
|
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 | Statement: [Novena to Our Lady of Lourdes, commonIntention, healing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonIntention Context triple: [Novena to Our Lady of Lourdes, commonIntention, healing]
-
A.
typicalIntentionsInclude
chosen
Indicates that one entity’s usual or characteristic intentions encompass or include the other entity or action.
-
B.
intendsTo
Indicates that one entity has the purpose, plan, or desire to perform an action involving another entity or outcome.
-
C.
intendedWith
Indicates that one entity is the planned or desired target, recipient, or context for the use or application of another entity.
-
D.
involvesIntendedVictim
Indicates that an action, event, or plan is directed toward and meant to affect a specific intended victim.
-
E.
patronIntention
Indicates that a patron has a specific intended action, purpose, or goal directed toward another entity or activity.
- 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_69e77e8046888190b07ffa58c7e2c37a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f67f0488bc819089fbd2d2478158d3 |
completed | May 2, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f67e3ed894819094c067c1ef624951 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 21, 2026, 8:03 p.m.