Triple
T8178916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Church of England clergy |
E191008
|
entity |
| Predicate | mayBeMarried |
P81281
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Church of England clergy, mayBeMarried, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayBeMarried Context triple: [Church of England clergy, mayBeMarried, true]
-
A.
acceptsMarriageTo
Indicates that one entity formally agrees to enter into a marriage with another entity.
-
B.
hasMarriage
Indicates a marital relationship exists between the two entities, specifying that they are or were legally married to each other.
-
C.
neverMarried
Indicates that the subject has not been legally married to any partner at any time up to the present.
-
D.
marital status
Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
-
E.
marriedIn
Indicates that two entities entered into a marital relationship at a specific place or within a particular jurisdiction.
- 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_69ca82c4538081909404325aa5639483 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4abd9768819091298e4dd995ac96 |
completed | March 31, 2026, 4:17 a.m. |
| PD | Predicate disambiguation | batch_69cb36a7952481908f34e3e82f375a84 |
completed | March 31, 2026, 2:51 a.m. |
| PDg | Predicate description generation | batch_69cb45503eec8190aeef0da6c3324710 |
completed | March 31, 2026, 3:53 a.m. |
Created at: March 30, 2026, 5:40 p.m.