Triple
T19268224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kirensk |
E481845
|
entity |
| Predicate | hasAirport |
P105
|
FINISHED |
| Object |
Kirensk Airport
Kirensk Airport is a regional public airport serving the town of Kirensk in Irkutsk Oblast, Russia, providing air transport connections for the surrounding area.
|
E1369284
|
NE FINISHED |
How this triple was built (4 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: Kirensk Airport | Statement: [Kirensk, hasAirport, Kirensk Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kirensk Airport Context triple: [Kirensk, hasAirport, Kirensk Airport]
-
A.
Staroselye Airport
Staroselye Airport is a regional airport serving the city of Rybinsk in Yaroslavl Oblast, Russia.
-
B.
Sokol Airport
Sokol Airport is the main airport serving the city of Magadan in Russia’s Far East, handling both domestic and limited international flights.
-
C.
Khrabrovo Airport
Khrabrovo Airport is the main civilian airport serving the Russian exclave of Kaliningrad and its surrounding region.
-
D.
Grabtsevo Airport
Grabtsevo Airport is the main commercial airport serving the city of Kaluga in western Russia, providing regional and limited international air connections.
-
E.
Ugolny Airport
Ugolny Airport is the main commercial airport serving the remote Arctic city of Anadyr in Russia’s Chukotka Autonomous Okrug.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kirensk Airport Triple: [Kirensk, hasAirport, Kirensk Airport]
Generated description
Kirensk Airport is a regional public airport serving the town of Kirensk in Irkutsk Oblast, Russia, providing air transport connections for the surrounding area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kirensk Airport Target entity description: Kirensk Airport is a regional public airport serving the town of Kirensk in Irkutsk Oblast, Russia, providing air transport connections for the surrounding area.
-
A.
Staroselye Airport
Staroselye Airport is a regional airport serving the city of Rybinsk in Yaroslavl Oblast, Russia.
-
B.
Sokol Airport
Sokol Airport is the main airport serving the city of Magadan in Russia’s Far East, handling both domestic and limited international flights.
-
C.
Khrabrovo Airport
Khrabrovo Airport is the main civilian airport serving the Russian exclave of Kaliningrad and its surrounding region.
-
D.
Grabtsevo Airport
Grabtsevo Airport is the main commercial airport serving the city of Kaluga in western Russia, providing regional and limited international air connections.
-
E.
Ugolny Airport
Ugolny Airport is the main commercial airport serving the remote Arctic city of Anadyr in Russia’s Chukotka Autonomous Okrug.
- F. None of above. chosen
Provenance (5 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fb8e1f888190a95f60fa29ca3b98 |
completed | April 20, 2026, 10:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07144768688190ab3c36d05b7d4e94 |
completed | May 15, 2026, 12:40 p.m. |
| NEDg | Description generation | batch_6a0715514bac8190aafb36b96d4b167d |
completed | May 15, 2026, 12:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07163cb15881908435e7d2fa68b06e |
completed | May 15, 2026, 12:49 p.m. |
Created at: April 10, 2026, 1:29 p.m.