Triple
T36166424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen of Technicolor |
E1046010
|
entity |
| Predicate | appliedToPersonReligion |
P110049
|
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: [Queen of Technicolor, appliedToPersonReligion, Christianity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliedToPersonReligion Context triple: [Queen of Technicolor, appliedToPersonReligion, Christianity]
-
A.
hasAssociatedReligion
Indicates that an entity is connected with or linked to a particular religion.
-
B.
namedForPersonReligion
Indicates that something is named after a person specifically because of that person's religious identity, role, or significance.
-
C.
relationshipToReligion
chosen
Indicates the nature or type of connection an entity has to a religion, such as affiliation, stance, or involvement.
-
D.
hasReligious
Indicates that an entity is associated with, practices, or adheres to a particular religion or religious affiliation.
-
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_69f76e396bc88190b99d221bff9be27a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff6fba1a5c8190a660279a6271d785 |
completed | May 9, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69ff6f59388c8190a7d6ab7bc7705bc0 |
completed | May 9, 2026, 5:31 p.m. |
Created at: May 3, 2026, 4:08 p.m.