Triple
T12774624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lydia Beardsall Lawrence |
E305334
|
entity |
| Predicate | religiousInclination |
P36791
|
FINISHED |
| Object | religiously inclined |
—
|
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: religiously inclined | Statement: [Lydia Beardsall Lawrence, religiousInclination, religiously inclined]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousInclination Context triple: [Lydia Beardsall Lawrence, religiousInclination, religiously inclined]
-
A.
religiousAttitude
chosen
Indicates an entity’s stance, disposition, or orientation toward religion or religious beliefs.
-
B.
religionOrBelief
Indicates that one entity holds, practices, or is associated with a particular religion, faith, or belief system.
-
C.
religiousAffiliation
Indicates that one entity has a specified religious association, belief system, or denominational membership.
-
D.
religiousMood
Indicates a prevailing emotional or spiritual atmosphere associated with religious experience, practice, or devotion between entities.
-
E.
religiousElement
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
- 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df6b3c88190b0bbe70de8ddcbf3 |
completed | April 10, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69d9640ba0688190973e4e7ec8d4a8e0 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:29 p.m.