Triple
T14700704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Islamic period |
E345288
|
entity |
| Predicate | hasKeyReligionAspect |
P27703
|
FINISHED |
| Object | monotheism |
—
|
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: monotheism | Statement: [Islamic period, hasKeyReligionAspect, monotheism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKeyReligionAspect Context triple: [Islamic period, hasKeyReligionAspect, monotheism]
-
A.
hasAssociatedReligion
Indicates that an entity is connected with or linked to a particular religion.
-
B.
hasReligiousType
Indicates that an entity is associated with or classified under a particular religion or religious category.
-
C.
hasReligiousSee
Indicates that one entity serves as the ecclesiastical or religious jurisdiction/seat (see) of another entity.
-
D.
hasReligiousCharacter
chosen
Indicates that an entity possesses a religious nature, function, or affiliation, or is characterized by religious aspects or significance.
-
E.
hasEponymReligion
Indicates that a religion is named after or derived from the name of a particular person.
- 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_69d822e4a8c08190a155df736bb7bc13 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb605f5948190ab6b20887c4b6833 |
completed | April 14, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69de657c57ec8190ae0b9bb79a514566 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:28 a.m.