Triple
T17868939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Fernando Cathedral Parish |
E446778
|
entity |
| Predicate | offersSacrament |
P94699
|
FINISHED |
| Object | Eucharist |
—
|
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: Eucharist | Statement: [San Fernando Cathedral Parish, offersSacrament, Eucharist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersSacrament Context triple: [San Fernando Cathedral Parish, offersSacrament, Eucharist]
-
A.
offersMinistry
chosen
Indicates that one entity provides or makes available a ministry or ministerial service to another entity.
-
B.
offersDestination
Indicates that one entity provides or makes available another entity as a possible destination.
-
C.
offersActivity
Indicates that one entity provides or makes available a specific activity for another entity to participate in or use.
-
D.
offersEdition
Indicates that one entity provides or makes available a particular version or edition of another entity.
-
E.
offersObject
Indicates that a subject provides or makes available a specific object to another party as an offer.
- 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_69d8b9f4c22c819093c2680434472894 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49aa18df881908a8ff40b7de19268 |
completed | April 19, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e6d2e88190ad9ef9f8a99f13e6 |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:18 a.m.