Triple
T3733887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince |
E79131
|
entity |
| Predicate | typicalReligionContext |
P51340
|
FINISHED |
| Object | hereditary monarchies worldwide |
—
|
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: hereditary monarchies worldwide | Statement: [Prince, typicalReligionContext, hereditary monarchies worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalReligionContext Context triple: [Prince, typicalReligionContext, hereditary monarchies worldwide]
-
A.
religiousCulturalContext
Indicates the religious or cultural setting, tradition, or framework within which an entity, practice, or event occurs or is interpreted.
-
B.
religionCommon
Indicates that the related entities share the same religion or religious affiliation.
-
C.
religiousTopicAddressed
Indicates that a subject deals with, discusses, or focuses on a religious theme, issue, or question.
-
D.
theologicalContext
Indicates the religious or doctrinal framework, tradition, or set of beliefs within which something (such as a text, event, or concept) is interpreted or understood.
-
E.
bearerReligion
Indicates that a bearer (such as a person or entity) adheres to, practices, or is associated with a particular religion.
- F. None of above. chosen
Provenance (4 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_69ad8b0e4650819090ad7cef094285e8 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb2457f08190a6b94e9895fced2c |
completed | March 8, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69adc04746588190b0dc535638f23546 |
completed | March 8, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69adc45debe48190b1c1f894e02b0316 |
completed | March 8, 2026, 6:47 p.m. |
Created at: March 8, 2026, 3:34 p.m.