Triple
T20319265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RIX |
E492163
|
entity |
| Predicate | usedInAirlineSchedulingSystems |
P83011
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [RIX, usedInAirlineSchedulingSystems, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInAirlineSchedulingSystems Context triple: [RIX, usedInAirlineSchedulingSystems, true]
-
A.
airlinesUse
Indicates that certain airlines operate, employ, or make use of a specified resource, service, or system.
-
B.
usedInFlightPlansFor
Indicates that something (e.g., data, a procedure, or a resource) is employed as part of creating or executing flight plans for specific flights or routes.
-
C.
usedByAirlineRole
Indicates that something (such as a resource, system, or process) is utilized by a specific role or position within an airline organization.
-
D.
usedInAirTrafficControlFor
Indicates that something serves as a tool, system, or resource specifically employed in the management, monitoring, or regulation of air traffic.
-
E.
associatedWithAirlineOperations
chosen
Indicates a relationship in which an entity is connected to, involved in, or relevant to the operations and activities of an airline.
- 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_69e0b4a0134081909113563e1c3ba68a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6778abd14819098a01fd32217fdde |
completed | April 20, 2026, 6:59 p.m. |
| PD | Predicate disambiguation | batch_69e55b23a0788190bf1853ef5b81823f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 16, 2026, 11:20 a.m.