Triple
T26853575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telmarines |
E676120
|
entity |
| Predicate | influenceOnSetting |
P157823
|
FINISHED |
| Object | turned Narnia into a more ordinary, less magical kingdom |
—
|
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: turned Narnia into a more ordinary, less magical kingdom | Statement: [Telmarines, influenceOnSetting, turned Narnia into a more ordinary, less magical kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influenceOnSetting Context triple: [Telmarines, influenceOnSetting, turned Narnia into a more ordinary, less magical kingdom]
-
A.
influencedAspectOf
chosen
Indicates that one entity has affected, shaped, or altered a particular aspect or component of another entity.
-
B.
incorporatesInfluence
Indicates that one entity integrates or absorbs the influence, ideas, or characteristics of another into itself.
-
C.
ruleInfluence
Indicates that one rule affects, constrains, or modifies the behavior, outcome, or applicability of another rule.
-
D.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
E.
coversSetting
Indicates that one entity includes or addresses a particular setting or context within its scope.
- 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_69eee9b9d7708190a15d7485709ae981 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f6a8df16a88190a23820e64a3b1f92 |
completed | May 3, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69f6a751d5e48190a77dcecbe7ef9f0b |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 27, 2026, 5:19 a.m.