Triple
T10992749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Personal Ordinariates |
E259788
|
entity |
| Predicate | shareMission |
P11707
|
FINISHED |
| Object | evangelization |
—
|
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: evangelization | Statement: [Personal Ordinariates, shareMission, evangelization]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shareMission Context triple: [Personal Ordinariates, shareMission, evangelization]
-
A.
sharesMission
chosen
Indicates that two or more entities are aligned in purpose, pursuing the same overarching mission or goal.
-
B.
shareFeature
Indicates that two or more entities possess at least one common attribute, property, or characteristic.
-
C.
sharesFeatureWith
Indicates that two entities have at least one common attribute, property, or characteristic in common.
-
D.
sharesModuleWith
Indicates that two entities are associated with or participate in at least one common module.
-
E.
sharesUniverseWith
Indicates that two entities exist within the same fictional or narrative universe, implying shared continuity, setting, or canon.
- 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d795d32f9081909def643571499521 |
completed | April 9, 2026, 12:04 p.m. |
| PD | Predicate disambiguation | batch_69d72e93ac648190b46c5d12bf3eb1e9 |
completed | April 9, 2026, 4:44 a.m. |
Created at: April 8, 2026, 9:24 p.m.