Triple
T5467499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luther College |
E122746
|
entity |
| Predicate | religiousLife |
P2154
|
FINISHED |
| Object | campus ministry programs |
—
|
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: campus ministry programs | Statement: [Luther College, religiousLife, campus ministry programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousLife Context triple: [Luther College, religiousLife, campus ministry programs]
-
A.
religiousActivity
Indicates participation in, performance of, or association with practices, rituals, or behaviors related to a religion or faith tradition.
-
B.
religiousTopicAddressed
Indicates that a subject deals with, discusses, or focuses on a religious theme, issue, or question.
-
C.
religiousElement
chosen
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
-
D.
religiousFunction
Indicates that one entity serves a religious role, purpose, or function in relation to another entity.
-
E.
religiousTarget
Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
- 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_69bd4643f16081908d7f29e08096115a |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd927c946c8190aef40679199fede3 |
completed | March 20, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69bd91a370a88190b5d17b8a5387138d |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:08 p.m.