Triple
T4592345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Nazarene College |
E103521
|
entity |
| Predicate | hasChapelRequirement |
P58182
|
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: [Eastern Nazarene College, hasChapelRequirement, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChapelRequirement Context triple: [Eastern Nazarene College, hasChapelRequirement, yes]
-
A.
hasChapelProgram
Indicates that an institution or organization offers or conducts a chapel program as part of its activities or services.
-
B.
hasChapels
Indicates that one entity contains, includes, or is associated with one or more chapels.
-
C.
hasChapelCountApprox
Indicates an approximate number of chapels associated with an entity.
-
D.
hasClergyRequirement
Indicates that a role, position, or activity requires the person involved to be a member of the clergy or to hold a specific clerical status.
-
E.
hasChapelArchitect
Indicates that an entity has another entity serving as the architect responsible for designing its chapel.
- 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_69bd43dccaf08190aa89e9991a289719 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd592520ec8190b1bd4cb4d9b94c94 |
completed | March 20, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69bd522acbcc8190bf24d9517793a2c1 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56b4a9508190acdb888eef18f1ee |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:11 p.m.