Triple
T19774669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diocese of Asia |
E474971
|
entity |
| Predicate | hadFiscalFunction |
P20953
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Diocese of Asia, hadFiscalFunction, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadFiscalFunction Context triple: [Diocese of Asia, hadFiscalFunction, yes]
-
A.
haveFiscalPowers
Indicates that an entity possesses legal authority or control over financial or budgetary matters.
-
B.
hadFunction
chosen
Indicates that an entity previously served or fulfilled a particular role, purpose, or function.
-
C.
hasBackOfficeFunctionsIn
Indicates that an entity’s back-office operations or support functions are performed or located in a specified place or organizational unit.
-
D.
hadJudicialFunction
Indicates that an entity exercised or was assigned an official judicial role, authority, or responsibility in relation to another entity or context.
-
E.
hasCommercialFunction
Indicates that an entity serves a commercial role or purpose, such as engaging in trade, sales, or other profit-oriented activities.
- 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_69d8e51a43a08190956bc6df13c91a77 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6535effcc819080a71de148759674 |
completed | April 20, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69e53053ed2881908400becdfada7fd3 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:48 p.m.