Triple
T341124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Egyptian National Police |
E6839
|
entity |
| Predicate | policeType |
P7908
|
FINISHED |
| Object | civilian police |
—
|
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: civilian police | Statement: [Egyptian National Police, policeType, civilian police]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policeType Context triple: [Egyptian National Police, policeType, civilian police]
-
A.
typeOfLawEnforcement
chosen
Indicates that one entity is a specific kind or category of law enforcement associated with another entity.
-
B.
policePrecinct
Indicates that a specified location, building, or area functions as or is designated as a police precinct.
-
C.
radarType
Indicates the specific category or classification of radar associated with an entity.
-
D.
securityAgency
Indicates that one entity functions as a security agency responsible for protection, surveillance, or enforcement activities in relation to another entity.
-
E.
typeOfDefense
Indicates the specific kind or category of defense employed or possessed in a given 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eae611f88190955fbebe2b01835b |
completed | Feb. 28, 2026, 1:17 p.m. |
| PD | Predicate disambiguation | batch_69a2e95197fc8190820e8ebd0d7d27fa |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.