Triple
T33123260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dominican Province of the Holy Rosary |
E847656
|
entity |
| Predicate | hasMissionaryCharacter |
P112782
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Dominican Province of the Holy Rosary, hasMissionaryCharacter, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMissionaryCharacter Context triple: [Dominican Province of the Holy Rosary, hasMissionaryCharacter, true]
-
A.
isMissionary
chosen
Indicates that an entity serves as a missionary, engaging in religious outreach or proselytizing activities toward others.
-
B.
hasClergyCharacter
Indicates that an entity possesses a religious or clerical role, status, or character.
-
C.
isMissionaryCircumstance
Indicates that a situation or context involves or is characterized by missionary activity or conditions related to missionary work.
-
D.
hasNotableMissionary
Indicates that an entity is associated with, or has, a notable missionary linked to it.
-
E.
hasClericalProtagonist
Indicates that the main character in the work is a member of the clergy or holds a religious office.
- 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_69f349588f088190b7c9588860f72033 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fbbc49da8c8190902bbb05d2477cab |
completed | May 6, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69fbb13f34b08190bbbb220ac1e6e666 |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 1, 2026, 1:27 a.m.