Triple
T36564940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diocese of Beijing |
E901947
|
entity |
| Predicate | hasOrdinaryForm |
P198562
|
FINISHED |
| Object | Roman Rite ordinary form |
—
|
NE NERFINISHED |
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: Roman Rite ordinary form | Statement: [Diocese of Beijing, hasOrdinaryForm, Roman Rite ordinary form]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOrdinaryForm Context triple: [Diocese of Beijing, hasOrdinaryForm, Roman Rite ordinary form]
-
A.
isOrdinaryOf
Indicates that one entity is the standard, non-special, or typical instance or form of another entity.
-
B.
hasNonStandardForm
Indicates that an entity possesses a form, variant, or representation that deviates from the standard, canonical, or commonly accepted form.
-
C.
hasNaturalForm
Indicates that an entity possesses an inherent, unaltered, or naturally occurring form or state.
-
D.
hasFormerOrdinary
Indicates that an entity previously held the status or role of an ordinary (e.g., a regular or standard office/position) in relation to another entity.
-
E.
hasFullForm
Indicates that one entity is the complete, expanded, or unabbreviated form of 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_69f76e6416708190a9754b8c52d4e453 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fef2db323c8190821bda53f22a42be |
completed | May 9, 2026, 8:39 a.m. |
| PD | Predicate disambiguation | batch_69fef21d63c88190abf6a99b59b3c655 |
completed | May 9, 2026, 8:36 a.m. |
| PDg | Predicate description generation | batch_69fef2da7d388190a5712a5094741f18 |
completed | May 9, 2026, 8:39 a.m. |
Created at: May 3, 2026, 4:11 p.m.