Triple
T1702525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brussels Airport |
E36797
|
entity |
| Predicate | hasSecurityIncidentDate |
P4332
|
FINISHED |
| Object | 22 March 2016 |
—
|
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: 22 March 2016 | Statement: [Brussels Airport, hasSecurityIncidentDate, 22 March 2016]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecurityIncidentDate Context triple: [Brussels Airport, hasSecurityIncidentDate, 22 March 2016]
-
A.
hasSecurityEvent
Indicates that a security-related incident or event is associated with, or has occurred for, a given entity.
-
B.
hasNotableIncident
Indicates that an entity is associated with a significant or noteworthy event, occurrence, or incident.
-
C.
attackDate
chosen
Indicates the calendar date on which an attack or assault event took place.
-
D.
notableProtectiveIncident
Indicates that a significant event occurred in which one entity protected or defended another in a notable or remarkable way.
-
E.
associatedWithCompromise
Indicates a relationship where an entity is linked to, involved in, or affected by a security compromise or breach.
- 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_69a88617439c819094ffb5d16a0f6307 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab75ad24408190814069e6e3ef9e59 |
completed | March 7, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69aa61bad17c8190861b92cfb423f68f |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.