Triple
T13829790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Reverend William Burks |
E332361
|
entity |
| Predicate | hasReligiousVocation |
P103888
|
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: [The Reverend William Burks, hasReligiousVocation, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousVocation Context triple: [The Reverend William Burks, hasReligiousVocation, yes]
-
A.
tookReligiousVowsOn
Indicates that an entity formally committed to religious vows on a specific date or occasion.
-
B.
tookReligiousVows
Indicates that an entity formally committed to a religious life by taking recognized vows within a religious tradition.
-
C.
hasReligiousOffice
chosen
Indicates that an entity holds or occupies a specific religious role, position, or office within a religious organization or tradition.
-
D.
hasReligiousRoleEquivalent
Indicates that two religious roles are considered functionally or hierarchically equivalent within or across religious traditions.
-
E.
hasClergy
Indicates that an organization or institution possesses or is served by members of the clergy.
- 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_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02970df88190a1bf35dffd131d9d |
completed | April 14, 2026, 9:02 a.m. |
| PD | Predicate disambiguation | batch_69dbc86668e08190ba9135d1c3f38d35 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:13 p.m.