Triple
T6941132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cairo West Air Base |
E160673
|
entity |
| Predicate | hasPerimeterSecurity |
P22957
|
FINISHED |
| Object | fenced and guarded facility |
—
|
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: fenced and guarded facility | Statement: [Cairo West Air Base, hasPerimeterSecurity, fenced and guarded facility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPerimeterSecurity Context triple: [Cairo West Air Base, hasPerimeterSecurity, fenced and guarded facility]
-
A.
hasSecurityPresence
chosen
Indicates that some form of security personnel, system, or measures are present at or associated with an entity or location.
-
B.
hasSecurityArea
Indicates that an entity is associated with, assigned to, or falls within a defined security-controlled area or zone.
-
C.
hasSecurityDimension
Indicates that something possesses or is associated with a particular aspect or dimension of security.
-
D.
hasSecurityArchitecture
Indicates that an entity is associated with or defined by a particular security architecture design or framework.
-
E.
hasSecurityNotion
Indicates that one entity possesses, defines, or is associated with a particular concept or notion of security in relation to another entity or 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_69c6884f3db4819080ad65da69386206 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e0c74fe48190aeaa018631e52ef6 |
completed | March 27, 2026, 7:55 p.m. |
| PD | Predicate disambiguation | batch_69c6d7bd5a388190a57a96d925696ff6 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:28 p.m.