Triple
T29600952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ali and Nino |
E754442
|
entity |
| Predicate | otherProtagonistReligion |
P11272
|
FINISHED |
| Object | Christianity |
—
|
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: Christianity | Statement: [Ali and Nino, otherProtagonistReligion, Christianity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: otherProtagonistReligion Context triple: [Ali and Nino, otherProtagonistReligion, Christianity]
-
A.
religionOfCharacterPortrayed
Indicates that a work portrays a character as adhering to or being associated with a particular religion.
-
B.
otherReligion
chosen
Indicates that one entity follows or is associated with a religion that is different from the religion of another entity.
-
C.
otherRivalReligion
Indicates that one entity follows or is associated with a religion that is a rival or competing faith to the religion associated with another entity.
-
D.
religiousOrMythicFigure
Indicates that the subject is regarded as a significant figure within a religious tradition or mythological system.
-
E.
laterReligion
Indicates that one religion or religious affiliation chronologically follows or replaces another for the same 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_69f0ef84e5d08190a0df17f5930ceed3 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f6c49627908190b3553474c7c3072b |
completed | May 3, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f23ae081909a52801266063a3c |
completed | May 3, 2026, 3:41 a.m. |
Created at: April 28, 2026, 6:22 p.m.