Triple
T33450020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nativity of Our Lord Parish |
E856609
|
entity |
| Predicate | hasLayRole |
P161
|
FINISHED |
| Object | parishioner |
—
|
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: parishioner | Statement: [Nativity of Our Lord Parish, hasLayRole, parishioner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLayRole Context triple: [Nativity of Our Lord Parish, hasLayRole, parishioner]
-
A.
hasPlayingRole
Indicates that an entity participates in an activity, event, or performance in a specific playing role or capacity.
-
B.
hasLegalRole
Indicates that an entity holds a specific legal capacity, status, or function in relation to another entity or context.
-
C.
mayHaveRole
Indicates that an entity is permitted or eligible to hold or perform a specified role.
-
D.
hasRole
chosen
Indicates that an entity occupies, performs, or is assigned a specific role or function in relation to another entity or context.
-
E.
hadStaffRole
Indicates that an entity served in a specific staff role or position for another entity during some period.
- 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_69f3497281a08190b4705de0b5f26ba7 |
completed | April 30, 2026, 12:22 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. |
Created at: May 1, 2026, 1:37 a.m.