Triple
T3219129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peelian principles of policing |
E67465
|
entity |
| Predicate | hasPrincipleCount |
P36421
|
FINISHED |
| Object | nine (commonly cited) principles |
—
|
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: nine (commonly cited) principles | Statement: [Peelian principles of policing, hasPrincipleCount, nine (commonly cited) principles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrincipleCount Context triple: [Peelian principles of policing, hasPrincipleCount, nine (commonly cited) principles]
-
A.
principlesCount
chosen
Indicates the number of principles associated with or applicable to a given entity or context.
-
B.
usesPrinciple
Indicates that one entity applies, relies on, or is based upon a particular principle in its functioning, reasoning, or design.
-
C.
recognizesPrinciple
Indicates that an entity acknowledges the validity, authority, or applicability of a particular principle.
-
D.
invokesPrinciple
Indicates that one entity calls upon, applies, or relies on a particular principle as the basis for an action, decision, or reasoning process.
-
E.
hasGradeCount
Indicates a relationship where an entity is associated with the number of grades it has or has received.
- 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_69ad858b8adc8190ad989712c87a476b |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adab0ef2c88190ab89e3217438a2bf |
completed | March 8, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69ad9e0bb6c48190a0659c67d40ee37c |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:08 p.m.