Triple
T360986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T5 |
E7849
|
entity |
| Predicate | hasSecurityZone |
P6793
|
FINISHED |
| Object | airside |
—
|
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: airside | Statement: [T5, hasSecurityZone, airside]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecurityZone Context triple: [T5, hasSecurityZone, airside]
-
A.
hasZone
chosen
Indicates that one entity possesses, contains, or is associated with a specific zone or designated area.
-
B.
hasProtectedArea
Indicates that an entity possesses, includes, or is associated with a designated protected area for conservation or restricted use.
-
C.
hasSecuritySupport
Indicates that one entity provides security-related assistance, maintenance, or protection services for another entity.
-
D.
hasFreeZone
Indicates that an entity includes or is associated with a designated free zone area where special rules, privileges, or exemptions apply.
-
E.
hasFareZone
Indicates that an entity is located within or associated with a specific fare zone used for pricing or ticketing.
- 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebce64c88190a0a8edcc7095f78b |
completed | Feb. 28, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69a2e95aeed48190b5e48865cc964938 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.