Triple
T38227831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temporary Home |
E1012196
|
entity |
| Predicate | religiousSubtext |
P47348
|
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: [Temporary Home, religiousSubtext, Christian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousSubtext Context triple: [Temporary Home, religiousSubtext, Christian]
-
A.
religiousTopicAddressed
chosen
Indicates that a subject deals with, discusses, or focuses on a religious theme, issue, or question.
-
B.
religiousDiscourseWith
Indicates that one entity engages in conversation or exchange specifically about religious topics with another entity.
-
C.
religiousElement
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
-
D.
subjectReligion
Indicates that the subject is associated with, practices, or adheres to a particular religion.
-
E.
religiousSpectrum
Indicates a relationship that places entities along a range or continuum of religious belief, practice, or affiliation.
- 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_69f76dd25e0c81909f2abd0803e5e3ee |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a00512437d48190ad20324968ead5f4 |
completed | May 10, 2026, 9:34 a.m. |
| PD | Predicate disambiguation | batch_6a0050227350819099f41369c3d168be |
completed | May 10, 2026, 9:30 a.m. |
Created at: May 3, 2026, 4:30 p.m.