Triple
T23915435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baptist conventions |
E602069
|
entity |
| Predicate | oftenElect |
P124802
|
FINISHED |
| Object | officers such as president and secretary |
—
|
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: officers such as president and secretary | Statement: [Baptist conventions, oftenElect, officers such as president and secretary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenElect Context triple: [Baptist conventions, oftenElect, officers such as president and secretary]
-
A.
oftenFrom
Indicates that something frequently originates, derives, or comes from a particular source or location.
-
B.
oftenHave
chosen
Indicates that one entity frequently possesses, experiences, or is associated with another entity.
-
C.
oftenUse
Indicates that one entity frequently or regularly uses, employs, or utilizes another entity.
-
D.
oftenSetIn
Indicates that something, such as a story or event, frequently takes place within a particular setting or context.
-
E.
oftenSays
Indicates that one entity frequently makes a particular statement or remark, or regularly expresses a certain idea or phrase.
- 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_69e2953a187081908346a9f36e85fc98 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1ce9917808190ad66a4e276a24b3d |
completed | April 29, 2026, 9:25 a.m. |
| PD | Predicate disambiguation | batch_69f16151ebdc819086e9e1d7cc1f4f3c |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:40 p.m.