Triple
T14049432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raymond Massey as Adam Trask |
E338044
|
entity |
| Predicate | characterReligionImplied |
P83945
|
FINISHED |
| Object | 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: Christian | Statement: [Raymond Massey as Adam Trask, characterReligionImplied, Christian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterReligionImplied Context triple: [Raymond Massey as Adam Trask, characterReligionImplied, Christian]
-
A.
religionOfCharacterPortrayed
chosen
Indicates that a work portrays a character as adhering to or being associated with a particular religion.
-
B.
characterBelief
Indicates that one character holds a belief, opinion, or assumption about another entity, situation, or proposition.
-
C.
hasReligiousCharacter
Indicates that an entity possesses a religious nature, function, or affiliation, or is characterized by religious aspects or significance.
-
D.
religiousCharacteristic
Indicates that one entity has a religious attribute, quality, or affiliation that characterizes or distinguishes it in a religious context.
-
E.
associatedReligionRole
Indicates that one entity holds a specific religious role, office, or function in relation to another entity.
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de3c88b5e48190b0f0149102c08992 |
completed | April 14, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69de05adef888190b023ab42ef5076b6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:20 p.m.