Triple
T20319263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RIX |
E492163
|
entity |
| Predicate | usedInAviationTicketing |
P7940
|
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, usedInAviationTicketing, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInAviationTicketing Context triple: [RIX, usedInAviationTicketing, true]
-
A.
usedInE-tickets
Indicates that something (such as a method, technology, or feature) is employed or applied within the context of electronic tickets (e-tickets).
-
B.
usedInRailwayTickets
Indicates that something is employed or applied in the context of railway tickets, such as their creation, validation, or usage.
-
C.
airlinesUse
Indicates that certain airlines operate, employ, or make use of a specified resource, service, or system.
-
D.
usedInAviation
chosen
Indicates that something is employed or applied within the field or context of aviation.
-
E.
airlineContext
Indicates a relationship, situation, or action that specifically occurs within or is constrained by an airline-related context (such as flights, carriers, or air travel operations).
- 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.