Triple
T34356931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shye Ben Tzur |
E881755
|
entity |
| Predicate | religiousOrSpiritualTheme |
P47348
|
FINISHED |
| Object | Sufism |
—
|
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: Sufism | Statement: [Shye Ben Tzur, religiousOrSpiritualTheme, Sufism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousOrSpiritualTheme Context triple: [Shye Ben Tzur, religiousOrSpiritualTheme, Sufism]
-
A.
religionOrBelief
Indicates that one entity holds, practices, or is associated with a particular religion, faith, or belief system.
-
B.
religiousElement
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
-
C.
religiousMood
Indicates a prevailing emotional or spiritual atmosphere associated with religious experience, practice, or devotion between entities.
-
D.
religiousSpectrum
Indicates a relationship that places entities along a range or continuum of religious belief, practice, or affiliation.
-
E.
religiousTopicAddressed
chosen
Indicates that a subject deals with, discusses, or focuses on a religious theme, issue, or question.
- 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_69f349bd06008190904c2f86c42749e3 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff70ecc1a481909571b18d56d982b8 |
completed | May 9, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69ff70322a3c8190837840ea42cd3093 |
completed | May 9, 2026, 5:34 p.m. |
Created at: May 1, 2026, 1:58 a.m.