Triple
T10726902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Humera |
E252971
|
entity |
| Predicate | hasAirport |
P105
|
FINISHED |
| Object |
Humera Airport
Humera Airport is a regional airport in northwestern Ethiopia that serves the town of Humera and its surrounding area.
|
E883134
|
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: Humera Airport | Statement: [Humera, hasAirport, Humera Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Humera Airport Context triple: [Humera, hasAirport, Humera Airport]
-
A.
Shah Makhdum Airport
Shah Makhdum Airport is a regional domestic airport serving the city of Rajshahi in western Bangladesh.
-
B.
Dalbandin Airport
Dalbandin Airport is a small domestic airport serving the town of Dalbandin in Balochistan, Pakistan, providing regional air connectivity.
-
C.
Chaghcharan Airport
Chaghcharan Airport is a small regional airport serving the town of Chaghcharan in central Afghanistan, providing vital air connectivity to this remote area.
-
D.
Punta Raisi Airport
Punta Raisi Airport is the main international airport serving Palermo and the surrounding region in Sicily, Italy.
-
E.
Sabha Airport
Sabha Airport is a public airport serving the city of Sabha in southwestern Libya, providing regional air transport connections for the surrounding Fezzan region.
- 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: Humera Airport Triple: [Humera, hasAirport, Humera Airport]
Generated description
Humera Airport is a regional airport in northwestern Ethiopia that serves the town of Humera and its surrounding area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Humera Airport Target entity description: Humera Airport is a regional airport in northwestern Ethiopia that serves the town of Humera and its surrounding area.
-
A.
Shah Makhdum Airport
Shah Makhdum Airport is a regional domestic airport serving the city of Rajshahi in western Bangladesh.
-
B.
Dalbandin Airport
Dalbandin Airport is a small domestic airport serving the town of Dalbandin in Balochistan, Pakistan, providing regional air connectivity.
-
C.
Chaghcharan Airport
Chaghcharan Airport is a small regional airport serving the town of Chaghcharan in central Afghanistan, providing vital air connectivity to this remote area.
-
D.
Punta Raisi Airport
Punta Raisi Airport is the main international airport serving Palermo and the surrounding region in Sicily, Italy.
-
E.
Sabha Airport
Sabha Airport is a public airport serving the city of Sabha in southwestern Libya, providing regional air transport connections for the surrounding Fezzan region.
- 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_69d6aa5d8be481909a43218b2bfdbe95 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d70fc713f081909ba1d1b986c1fe5c |
completed | April 9, 2026, 2:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de2297f7a48190b194f7e611d0682b |
completed | April 14, 2026, 11:18 a.m. |
| NEDg | Description generation | batch_69de25d25474819081402b75ef7492f6 |
completed | April 14, 2026, 11:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69de2808244c8190bdb2d4d49f30e0d7 |
completed | April 14, 2026, 11:42 a.m. |
Created at: April 8, 2026, 9:14 p.m.