Triple
T20354252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kapan |
E496099
|
entity |
| Predicate | hasAirport |
P105
|
FINISHED |
| Object |
Kapan Airport
Kapan Airport is a small regional airport serving the town of Kapan in southern Armenia, primarily handling domestic flights.
|
E1432316
|
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: Kapan Airport | Statement: [Kapan, hasAirport, Kapan Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kapan Airport Context triple: [Kapan, hasAirport, Kapan Airport]
-
A.
Iki Airport
Iki Airport is a regional airport in Nagasaki Prefecture, Japan, providing air transport services to and from Iki Island.
-
B.
Heho Airport
Heho Airport is a regional airport in Myanmar that serves as the main air gateway to Taunggyi and the nearby Inle Lake area.
-
C.
Muanda Airport
Muanda Airport is a public airport serving the coastal town of Muanda in the western Democratic Republic of the Congo, providing regional air connectivity for passengers and cargo.
-
D.
Kapit Airport
Kapit Airport is a small regional airport in Sarawak, Malaysia, serving the town of Kapit and surrounding interior communities.
-
E.
Ramingining Airport
Ramingining Airport is a small regional airfield serving the remote Aboriginal community of Ramingining in the Northern Territory of Australia.
- 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: Kapan Airport Triple: [Kapan, hasAirport, Kapan Airport]
Generated description
Kapan Airport is a small regional airport serving the town of Kapan in southern Armenia, primarily handling domestic flights.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kapan Airport Target entity description: Kapan Airport is a small regional airport serving the town of Kapan in southern Armenia, primarily handling domestic flights.
-
A.
Iki Airport
Iki Airport is a regional airport in Nagasaki Prefecture, Japan, providing air transport services to and from Iki Island.
-
B.
Heho Airport
Heho Airport is a regional airport in Myanmar that serves as the main air gateway to Taunggyi and the nearby Inle Lake area.
-
C.
Muanda Airport
Muanda Airport is a public airport serving the coastal town of Muanda in the western Democratic Republic of the Congo, providing regional air connectivity for passengers and cargo.
-
D.
Kapit Airport
Kapit Airport is a small regional airport in Sarawak, Malaysia, serving the town of Kapit and surrounding interior communities.
-
E.
Ramingining Airport
Ramingining Airport is a small regional airfield serving the remote Aboriginal community of Ramingining in the Northern Territory of Australia.
- 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_69e0b4a3f7f48190b37f354574028ca6 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67852ca9881908a5af18005639859 |
completed | April 20, 2026, 7:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a088afea7388190b799a3692b2226d1 |
completed | May 16, 2026, 3:19 p.m. |
| NEDg | Description generation | batch_6a088bc432008190943421af77787f55 |
completed | May 16, 2026, 3:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a088c42288c8190805bdbe6e8ef184b |
completed | May 16, 2026, 3:24 p.m. |
Created at: April 16, 2026, 11:25 a.m.