Triple
T29653951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benedict Tigers |
E750215
|
entity |
| Predicate | sponsorInstitutionReligiousAffiliation |
P20650
|
FINISHED |
| Object | Christian |
—
|
NE NERFINISHED |
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: Christian | Statement: [Benedict Tigers, sponsorInstitutionReligiousAffiliation, Christian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sponsorInstitutionReligiousAffiliation Context triple: [Benedict Tigers, sponsorInstitutionReligiousAffiliation, Christian]
-
A.
religiousInstitutionLinked
Indicates that there is an established connection or association between a religious institution and another entity.
-
B.
hasParentInstitutionReligiousAffiliation
Indicates that an institution’s parent organization is associated with a particular religious affiliation.
-
C.
hasReligiousSponsor
chosen
Indicates that an entity is financially or organizationally supported by a religious individual, group, or institution.
-
D.
religiousInstitutionShared
Indicates that two entities are associated with or participate in the same religious institution or organization.
-
E.
hasReligiousOrganization
Indicates that an entity is associated with, governed by, or belongs to a specific religious organization.
- 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_69f0d6226fe881908819197c9ef9ee04 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f67d3624248190a36a9b2d2e9778d4 |
completed | May 2, 2026, 10:39 p.m. |
| PD | Predicate disambiguation | batch_69f678ce54b081908c26edfd49e39c60 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 28, 2026, 6:54 p.m.