Triple
T33439582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marian apparitions of 1877 |
E856322
|
entity |
| Predicate | hasMessageContent |
P198270
|
FINISHED |
| Object | encouragement to trust in God |
—
|
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: encouragement to trust in God | Statement: [Marian apparitions of 1877, hasMessageContent, encouragement to trust in God]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMessageContent Context triple: [Marian apparitions of 1877, hasMessageContent, encouragement to trust in God]
-
A.
hasPayload
Indicates that one entity carries, contains, or is equipped with another entity as its payload.
-
B.
hasMessageNumber
Indicates that an entity is associated with a specific message identified by a particular number in a sequence or set.
-
C.
hasContentType
Indicates that an entity is associated with or classified by a specific type of content.
-
D.
hasMessageSender
Indicates that one entity is the sender or originator of a given message.
-
E.
hasContentFrom
Indicates that one entity’s content is derived from, includes, or is based on another entity.
- 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_69f34971b75881908be360bb041f003c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fed6da0390819096b88ef4714b144e |
completed | May 9, 2026, 6:40 a.m. |
| PD | Predicate disambiguation | batch_69fed53517d081909966f31707625f1a |
completed | May 9, 2026, 6:33 a.m. |
| PDg | Predicate description generation | batch_69fed6d90f2081909cd21e5e973a6b89 |
completed | May 9, 2026, 6:40 a.m. |
Created at: May 1, 2026, 1:37 a.m.