Triple
T2295298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turkish Airlines |
E51598
|
entity |
| Predicate | destinationCount |
P13065
|
FINISHED |
| Object | over 300 destinations |
—
|
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: over 300 destinations | Statement: [Turkish Airlines, destinationCount, over 300 destinations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: destinationCount Context triple: [Turkish Airlines, destinationCount, over 300 destinations]
-
A.
servesDestinationCount
chosen
Indicates the number of distinct destinations that an entity (such as a service, route, or provider) serves.
-
B.
numberOfRoutes
Indicates the total count of distinct routes or paths associated with a given entity or between specified entities.
-
C.
journeyDestination
Indicates that one entity serves as the endpoint or intended destination of another entity’s journey or travel.
-
D.
destinationCity
Indicates the city to which an entity is traveling, being sent, or ultimately directed.
-
E.
numberOfHostCities
Indicates the count of distinct cities that have hosted or will host a particular event or activity.
- 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_69a88b0a9f248190bcff941463d8f65a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abcd0e42248190ada33b84d75caa64 |
completed | March 7, 2026, 7 a.m. |
| PD | Predicate disambiguation | batch_69abc589295c819092989820c2b4e9d8 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.