Triple
T524802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liberal Friends |
E10893
|
entity |
| Predicate | interfaithAttitude |
P6264
|
FINISHED |
| Object | open to insights from other religions |
—
|
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: open to insights from other religions | Statement: [Liberal Friends, interfaithAttitude, open to insights from other religions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interfaithAttitude Context triple: [Liberal Friends, interfaithAttitude, open to insights from other religions]
-
A.
religiousReception
Indicates a relationship where one entity formally receives, welcomes, or hosts another in a specifically religious or faith-based context.
-
B.
religiousAffiliation
Indicates that one entity has a specified religious association, belief system, or denominational membership.
-
C.
hadViewOnReligion
chosen
Indicates that an entity held a particular perspective, belief, or stance regarding religion.
-
D.
influencedReligion
Indicates that one entity has had a shaping or modifying effect on the religious beliefs, practices, or traditions of another entity.
-
E.
religionMinority
Indicates that the subject’s religion is a minority faith within the relevant population or context.
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1b656c08190b387f21b06d99e68 |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f0198ecc8190883849e5a8245963 |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.