Triple
T14276311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prydonian Chapter |
E353924
|
entity |
| Predicate | influenceLevel |
P63994
|
FINISHED |
| Object | most powerful Time Lord Chapter |
—
|
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: most powerful Time Lord Chapter | Statement: [Prydonian Chapter, influenceLevel, most powerful Time Lord Chapter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influenceLevel Context triple: [Prydonian Chapter, influenceLevel, most powerful Time Lord Chapter]
-
A.
typeOfInfluence
Indicates the specific nature or category of influence that one entity exerts on another.
-
B.
typicalLevelOfInfluence
chosen
Indicates the usual degree or strength of influence one entity exerts over another or within a given context.
-
C.
influentialFrom
Indicates that one entity has exerted influence on another, contributing to or shaping the latter’s ideas, behavior, or development.
-
D.
hasSignificantInfluenceIn
Indicates that one entity exerts a substantial impact or shaping effect on another entity within a particular domain, context, or outcome.
-
E.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
- 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6583f0ec81909ebfc7a2c6351ff8 |
completed | April 14, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69de2a88446481909cd526da97a3b70f |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:10 a.m.