Triple
T22953669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karima |
E570089
|
entity |
| Predicate | hasNearbyAirport |
P4363
|
FINISHED |
| Object |
Merowe Airport
Merowe Airport is a regional airport in northern Sudan that serves the town of Karima and the surrounding area near the Nile.
|
E1562790
|
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: Merowe Airport | Statement: [Karima, hasNearbyAirport, Merowe Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Merowe Airport Context triple: [Karima, hasNearbyAirport, Merowe Airport]
-
A.
Kufra Airport
Kufra Airport is a public airport serving the remote town of Al Kufrah in southeastern Libya, providing vital regional and domestic air connectivity.
-
B.
Abu Simbel Airport
Abu Simbel Airport is a small regional airport in southern Egypt that serves tourists visiting the nearby Abu Simbel temples and surrounding area.
-
C.
La Nubia Airport
La Nubia Airport is a small regional airport serving the city of Manizales in Colombia’s coffee-growing region.
-
D.
Mehamn Airport
Mehamn Airport is a regional airport in northern Norway serving the village of Mehamn and surrounding communities in Finnmark.
-
E.
El-Obeid Airport
El-Obeid Airport is a public airport serving the city of El-Obeid and the surrounding region in central Sudan.
- 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: Merowe Airport Triple: [Karima, hasNearbyAirport, Merowe Airport]
Generated description
Merowe Airport is a regional airport in northern Sudan that serves the town of Karima and the surrounding area near the Nile.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Merowe Airport Target entity description: Merowe Airport is a regional airport in northern Sudan that serves the town of Karima and the surrounding area near the Nile.
-
A.
Kufra Airport
Kufra Airport is a public airport serving the remote town of Al Kufrah in southeastern Libya, providing vital regional and domestic air connectivity.
-
B.
Abu Simbel Airport
Abu Simbel Airport is a small regional airport in southern Egypt that serves tourists visiting the nearby Abu Simbel temples and surrounding area.
-
C.
La Nubia Airport
La Nubia Airport is a small regional airport serving the city of Manizales in Colombia’s coffee-growing region.
-
D.
Mehamn Airport
Mehamn Airport is a regional airport in northern Norway serving the village of Mehamn and surrounding communities in Finnmark.
-
E.
El-Obeid Airport
El-Obeid Airport is a public airport serving the city of El-Obeid and the surrounding region in central Sudan.
- 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_69e2459199d08190a8184ee2aa935842 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181ef7db4819093ab8117ed53c174 |
completed | April 29, 2026, 3:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0bca19d3088190b62c3c71d7c5fa47 |
completed | May 19, 2026, 2:25 a.m. |
| NEDg | Description generation | batch_6a0bcaf9d50481908e4c451048f4018a |
completed | May 19, 2026, 2:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0bcb5f72708190b4829fd6c3447879 |
completed | May 19, 2026, 2:30 a.m. |
Created at: April 17, 2026, 3:46 p.m.