Triple
T2545031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Archbishop of Córdoba |
E57877
|
entity |
| Predicate | hasPastoralCareOf |
P18415
|
FINISHED |
| Object | Catholic faithful in the Archdiocese of Córdoba |
—
|
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: Catholic faithful in the Archdiocese of Córdoba | Statement: [Archbishop of Córdoba, hasPastoralCareOf, Catholic faithful in the Archdiocese of Córdoba]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPastoralCareOf Context triple: [Archbishop of Córdoba, hasPastoralCareOf, Catholic faithful in the Archdiocese of Córdoba]
-
A.
hasPastoralMission
chosen
Indicates that an entity is responsible for providing spiritual care, guidance, or religious leadership to a community or group.
-
B.
hasPaddock
Indicates that one entity possesses or is associated with a specific paddock area or enclosure.
-
C.
hadOrgan
Indicates that an entity previously possessed or contained a specific organ as part of its body.
-
D.
hasHistoryOf
Indicates that an entity has a documented prior occurrence or background of a specified condition, event, or state.
-
E.
hasPetForm
Indicates that one entity can transform into or assume the form of another entity that is characterized as a pet.
- 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_69ab4a5212d88190b989ce129f2ad87f |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd2c285288190b41fc0188879623a |
completed | March 7, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69abd0c63964819092d5f578195ae8dd |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:47 p.m.