Triple
T431748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Episcopal Diocese of New York |
E9727
|
entity |
| Predicate | hasParishType |
P13874
|
FINISHED |
| Object | urban parishes |
—
|
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: urban parishes | Statement: [Episcopal Diocese of New York, hasParishType, urban parishes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParishType Context triple: [Episcopal Diocese of New York, hasParishType, urban parishes]
-
A.
hasClergyType
Indicates the specific category or role of clergy associated with an entity.
-
B.
hasMunicipalityType
Indicates that an administrative unit is classified as having a specific type or category of municipality (e.g., city, town, village).
-
C.
hasCivilParishStatus
Indicates that an entity holds the official administrative status or designation of a civil parish.
-
D.
hasCemeteryType
Indicates that a cemetery is classified as belonging to a specific type or category of cemetery.
-
E.
parish
Indicates that an entity is administratively or ecclesiastically associated with a particular parish.
- 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_69a2e801e1d48190b505d1dd336b52ac |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eef07e748190b05392778f3de980 |
completed | Feb. 28, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69a2edd9264c8190b92f9a50348e5541 |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eeb93584819082f23eff13e17c4f |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.