Triple
T19322528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rex Nemorensis |
E483261
|
entity |
| Predicate | centralExampleFor |
P127119
|
FINISHED |
| Object | James George Frazer's theory of myth and magic |
—
|
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: James George Frazer's theory of myth and magic | Statement: [Rex Nemorensis, centralExampleFor, James George Frazer's theory of myth and magic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: centralExampleFor Context triple: [Rex Nemorensis, centralExampleFor, James George Frazer's theory of myth and magic]
-
A.
centralExample
chosen
Indicates that one entity serves as the primary or most representative example of another entity or concept.
-
B.
centralIn
Indicates that one entity occupies a central or most important position within another entity, context, or structure.
-
C.
majorExample
Indicates that one entity serves as a primary or most significant example or instance of another entity.
-
D.
baseExamples
Indicates that something serves as a fundamental or illustrative example for understanding or demonstrating another concept, item, or case.
-
E.
standardExample
Indicates that something is a typical or canonical instance used to illustrate a general case or concept.
- 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_69d8e8d13e3c81909d91d1d5ec37c095 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e60d8948948190b76a384041333509 |
completed | April 20, 2026, 11:27 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0ef66881909d489d634eee817a |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:32 p.m.