Triple
T30778483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diocese of Chartres |
E783743
|
entity |
| Predicate | languageOfPastoralWork |
P51876
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Diocese of Chartres, languageOfPastoralWork, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfPastoralWork Context triple: [Diocese of Chartres, languageOfPastoralWork, French]
-
A.
lenguaDeTrabajo
Indicates that something functions as a working language used for communication in a specific context or setting.
-
B.
languageFamilyOfWork
Indicates that a work belongs to or is classified under a particular language family.
-
C.
usedVernacularInPastoralCare
chosen
Indicates that someone employed the local or common spoken language when providing pastoral care or spiritual guidance.
-
D.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another entity.
-
E.
languageOfUnderlyingWork
Indicates the language in which the original or underlying work (from which a derived or related work stems) is expressed.
- 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_69f224b213c8819083886073f90b647e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ff38b960808190a8263348f1e5c0e4 |
completed | May 9, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69ff37d97d9c8190849b2bac14f9af1d |
completed | May 9, 2026, 1:34 p.m. |
Created at: April 29, 2026, 8:41 p.m.