Triple
T4945986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agnes Jemima |
E111050
|
entity |
| Predicate | givesPerspectiveOn |
P8789
|
FINISHED |
| Object | theocratic regime of Gilead |
—
|
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: theocratic regime of Gilead | Statement: [Agnes Jemima, givesPerspectiveOn, theocratic regime of Gilead]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: givesPerspectiveOn Context triple: [Agnes Jemima, givesPerspectiveOn, theocratic regime of Gilead]
-
A.
perspectiveOf
chosen
Indicates that something is expressed, depicted, or understood from the viewpoint or standpoint of a particular entity.
-
B.
useOfPerspective
Indicates that one entity adopts or applies a particular visual, narrative, or conceptual viewpoint in relation to another entity or context.
-
C.
givesOpinionOn
Indicates that one entity expresses a view, judgment, or evaluation about another entity or subject.
-
D.
providesExposureTo
Indicates that one entity gives another entity the opportunity to be seen, noticed, or become known by a particular audience, environment, or set of influences.
-
E.
providesInformationIn
Indicates that one entity supplies or conveys information within or through another entity or context.
- 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_69bd441721cc819085c7e33fe0876818 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd70aa890c81908e685ec5e88cae1f |
completed | March 20, 2026, 4:07 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3aa1388190b3e0c8ee1ba1e4fa |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:31 p.m.