Triple
T28574013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lufthansa heist |
E723184
|
entity |
| Predicate | airportEmployeeInvolved |
P5148
|
FINISHED |
| Object | Louis Werner |
—
|
NE NERFINISHED |
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: Louis Werner | Statement: [Lufthansa heist, airportEmployeeInvolved, Louis Werner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportEmployeeInvolved Context triple: [Lufthansa heist, airportEmployeeInvolved, Louis Werner]
-
A.
associatedWithAirportRole
Indicates a relationship where an entity is linked to a specific functional role or responsibility within an airport context.
-
B.
airportRole
chosen
Indicates that an entity serves a specific functional role or capacity within the context of an airport.
-
C.
officeInvolved
Indicates that a particular office or organizational unit is involved or participates in a specified event, action, or relationship.
-
D.
authorizedPersonnel
Indicates that the referenced entity is officially permitted or empowered to access, use, or perform actions within a specified system, resource, or context.
-
E.
associatedWithFlight
Indicates a relationship where an entity is linked or connected to a specific flight, such as by participation, operation, or relevance.
- 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_69f01d7e97708190ae9e77ee66a68abd |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 28, 2026, 4:11 a.m.