Triple
T34112720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helen Graham |
E874879
|
entity |
| Predicate | religiousBeliefInFiction |
P83945
|
FINISHED |
| Object | devout Christian |
—
|
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: devout Christian | Statement: [Helen Graham, religiousBeliefInFiction, devout Christian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousBeliefInFiction Context triple: [Helen Graham, religiousBeliefInFiction, devout Christian]
-
A.
religiousDenominationInFiction
Indicates that a fictional work, character, or setting is associated with or depicts a particular religious denomination.
-
B.
religiousIdeologyInFiction
Indicates that a religious ideology is depicted, referenced, or plays a role within a fictional work or narrative.
-
C.
religiousRoleInFiction
Indicates that an entity holds or performs a religious role or function within a fictional context or narrative.
-
D.
religionOfCharacterPortrayed
chosen
Indicates that a work portrays a character as adhering to or being associated with a particular religion.
-
E.
religionOrBelief
Indicates that one entity holds, practices, or is associated with a particular religion, faith, or belief system.
- 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_69f349a80d4481908527317d43f5c579 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff64b957bc81908afbc5914234a8ea |
completed | May 9, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69ff6446593c81909173e296eea2590c |
completed | May 9, 2026, 4:43 p.m. |
Created at: May 1, 2026, 1:53 a.m.