Triple
T614397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Catholic Church of the Czech Republic |
E12170
|
entity |
| Predicate | clergyCan |
P17130
|
FINISHED |
| Object | marry |
—
|
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: marry | Statement: [Old Catholic Church of the Czech Republic, clergyCan, marry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clergyCan Context triple: [Old Catholic Church of the Czech Republic, clergyCan, marry]
-
A.
hasClergy
Indicates that an organization or institution possesses or is served by members of the clergy.
-
B.
clergyPractice
Indicates that a member of the clergy engages in, performs, or follows a particular religious practice or ritual.
-
C.
hasClergyType
Indicates the specific category or role of clergy associated with an entity.
-
D.
religiousAdministration
Indicates that one entity holds authority or responsibility for managing, overseeing, or governing the religious affairs, practices, or institutions of another entity.
-
E.
hasClergyOrder
Indicates that an entity is associated with, or belongs to, a specific religious or clerical order.
- 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49e0a0f588190b953fdb585263307 |
completed | March 1, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69a49cfbcbf88190a854921dc531eba8 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49def31ec81909dc53e70f4a36eda |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:35 p.m.