Triple
T10301151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Farah Province |
E241629
|
entity |
| Predicate | hasAirport |
P105
|
FINISHED |
| Object |
Farah Airport
Farah Airport is a small regional airport serving the city and surrounding areas of Farah Province in western Afghanistan.
|
E856473
|
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: Farah Airport | Statement: [Farah Province, hasAirport, Farah Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Farah Airport Context triple: [Farah Province, hasAirport, Farah Airport]
-
A.
Sania Ramel Airport
Sania Ramel Airport is a regional airport serving the city of Tétouan in northern Morocco, providing domestic and limited international flights.
-
B.
Jowhar Airport
Jowhar Airport is a public airfield serving the town of Jowhar in Somalia, providing regional air transport connections.
-
C.
Gardabya Airport
Gardabya Airport is a Libyan airport serving the coastal city of Sirte and its surrounding region.
-
D.
Saidu Sharif Airport
Saidu Sharif Airport is a regional airport serving the town of Saidu Sharif and the surrounding Swat Valley region in Khyber Pakhtunkhwa, Pakistan.
-
E.
Ha'il Regional Airport
Ha'il Regional Airport is a public airport serving the city of Ha'il and its surrounding region in northwestern Saudi Arabia, handling domestic flights and regional air traffic.
- 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: Farah Airport Triple: [Farah Province, hasAirport, Farah Airport]
Generated description
Farah Airport is a small regional airport serving the city and surrounding areas of Farah Province in western Afghanistan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Farah Airport Target entity description: Farah Airport is a small regional airport serving the city and surrounding areas of Farah Province in western Afghanistan.
-
A.
Sania Ramel Airport
Sania Ramel Airport is a regional airport serving the city of Tétouan in northern Morocco, providing domestic and limited international flights.
-
B.
Jowhar Airport
Jowhar Airport is a public airfield serving the town of Jowhar in Somalia, providing regional air transport connections.
-
C.
Gardabya Airport
Gardabya Airport is a Libyan airport serving the coastal city of Sirte and its surrounding region.
-
D.
Saidu Sharif Airport
Saidu Sharif Airport is a regional airport serving the town of Saidu Sharif and the surrounding Swat Valley region in Khyber Pakhtunkhwa, Pakistan.
-
E.
Ha'il Regional Airport
Ha'il Regional Airport is a public airport serving the city of Ha'il and its surrounding region in northwestern Saudi Arabia, handling domestic flights and regional air traffic.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2eefe8881908a672c4dca7657ca |
completed | April 7, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71d47049c81909b60058c36042f71 |
completed | April 9, 2026, 3:30 a.m. |
| NEDg | Description generation | batch_69d7318402f08190b655bdddbd97ecb9 |
completed | April 9, 2026, 4:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d734473ef48190852dbe48742a4273 |
completed | April 9, 2026, 5:08 a.m. |
Created at: April 6, 2026, 11:44 a.m.