Triple
T22734396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lar |
E562224
|
entity |
| Predicate | transportInfrastructure |
P1777
|
FINISHED |
| Object |
Lar Airport
Lar Airport is a regional airport serving the city of Lar and its surrounding area in southern Iran.
|
E1552306
|
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: Lar Airport | Statement: [Lar, transportInfrastructure, Lar Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lar Airport Context triple: [Lar, transportInfrastructure, Lar Airport]
-
A.
Trang Airport
Trang Airport is a domestic airport in Trang Province, southern Thailand, serving as the main air gateway to the city of Trang and nearby coastal and island destinations.
-
B.
Tari Airport
Tari Airport is a regional airfield serving the town of Tari and surrounding areas in Hela Province, Papua New Guinea.
-
C.
Lawas Airport
Lawas Airport is a small regional airport in Sarawak, Malaysia, serving the town of Lawas and connecting it to other destinations in the region.
-
D.
Loakan Airport
Loakan Airport is a small domestic airport serving the city of Baguio in the mountainous Cordillera region of the Philippines.
-
E.
Lumbia Airport
Lumbia Airport was the former main airport serving Cagayan de Oro in the Philippines before being supplanted by the newer Laguindingan Airport.
- 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: Lar Airport Triple: [Lar, transportInfrastructure, Lar Airport]
Generated description
Lar Airport is a regional airport serving the city of Lar and its surrounding area in southern Iran.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lar Airport Target entity description: Lar Airport is a regional airport serving the city of Lar and its surrounding area in southern Iran.
-
A.
Trang Airport
Trang Airport is a domestic airport in Trang Province, southern Thailand, serving as the main air gateway to the city of Trang and nearby coastal and island destinations.
-
B.
Tari Airport
Tari Airport is a regional airfield serving the town of Tari and surrounding areas in Hela Province, Papua New Guinea.
-
C.
Lawas Airport
Lawas Airport is a small regional airport in Sarawak, Malaysia, serving the town of Lawas and connecting it to other destinations in the region.
-
D.
Loakan Airport
Loakan Airport is a small domestic airport serving the city of Baguio in the mountainous Cordillera region of the Philippines.
-
E.
Lumbia Airport
Lumbia Airport was the former main airport serving Cagayan de Oro in the Philippines before being supplanted by the newer Laguindingan Airport.
- 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_69e24550859c81908727d91efc3a81b4 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1796e4970819090fb9c9926673938 |
completed | April 29, 2026, 3:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b8fca5f10819083604273aae3fcc3 |
completed | May 18, 2026, 10:16 p.m. |
| NEDg | Description generation | batch_6a0b93bc59e481909e2fbee11a29b7a9 |
completed | May 18, 2026, 10:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b9488db048190b73ff89215ffeb74 |
completed | May 18, 2026, 10:36 p.m. |
Created at: April 17, 2026, 3:22 p.m.