Triple
T5777414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tupolev Tu-204 |
E127477
|
entity |
| Predicate | airlineServiceEntry |
P66394
|
FINISHED |
| Object | with Russian carrier Vnukovo Airlines |
—
|
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: with Russian carrier Vnukovo Airlines | Statement: [Tupolev Tu-204, airlineServiceEntry, with Russian carrier Vnukovo Airlines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlineServiceEntry Context triple: [Tupolev Tu-204, airlineServiceEntry, with Russian carrier Vnukovo Airlines]
-
A.
airlineService
Indicates that an airline operates transportation services (such as flights) between specified locations or for specified routes.
-
B.
servesAirline
Indicates that a transportation facility or location provides service for, or is regularly used by, a specified airline.
-
C.
servesAirlineType
Indicates that a service provider (such as an airport, terminal, or facility) accommodates or operates flights for a specified type or category of airline.
-
D.
airlineHub
Indicates that a particular location (typically an airport or city) serves as a central hub or primary operational base for an airline.
-
E.
airline
Indicates that an entity operates as a commercial air transport carrier providing flight services between locations.
- F. None of above. chosen
Provenance (4 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_69c008361fa88190aefa4dc41b051e7f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02acb12c081908e4beee4a957f9f9 |
completed | March 22, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69c021d0c6088190ba670ddcdbf5ca3e |
completed | March 22, 2026, 5:07 p.m. |
| PDg | Predicate description generation | batch_69c02ac9603481909e3fa295d7904a15 |
completed | March 22, 2026, 5:45 p.m. |
Created at: March 22, 2026, 3:50 p.m.