Triple
T15531975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ålesund Airport, Vigra |
E370241
|
entity |
| Predicate | ICAOcode |
P419
|
FINISHED |
| Object |
ENAL
ENAL is the ICAO airport code for Ålesund Airport, Vigra, a regional airport serving the Ålesund area in Norway.
|
E1162631
|
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: ENAL | Statement: [Ålesund Airport, Vigra, ICAOcode, ENAL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ENAL Context triple: [Ålesund Airport, Vigra, ICAOcode, ENAL]
-
A.
ENAS
ENAS (Efficient Neural Architecture Search) is a method that dramatically reduces the computational cost of neural architecture search by sharing parameters among many candidate architectures within a single super-network.
-
B.
ENK
ENK is the ICAO airline designator assigned to Equair, an Ecuadorian commercial airline.
-
C.
ENRA
ENRA is the ICAO airport code for Mo i Rana Airport, Røssvoll in Norway.
-
D.
ANLE
ANLE is the North American Academy of the Spanish Language, an institution dedicated to studying, preserving, and promoting the correct use of Spanish in the United States.
-
E.
ENH
ENH is the IATA airport code for Enshi Xujiaping Airport, a regional airport serving Enshi in Hubei Province, China.
- 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: ENAL Triple: [Ålesund Airport, Vigra, ICAOcode, ENAL]
Generated description
ENAL is the ICAO airport code for Ålesund Airport, Vigra, a regional airport serving the Ålesund area in Norway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ENAL Target entity description: ENAL is the ICAO airport code for Ålesund Airport, Vigra, a regional airport serving the Ålesund area in Norway.
-
A.
ENAS
ENAS (Efficient Neural Architecture Search) is a method that dramatically reduces the computational cost of neural architecture search by sharing parameters among many candidate architectures within a single super-network.
-
B.
ENK
ENK is the ICAO airline designator assigned to Equair, an Ecuadorian commercial airline.
-
C.
ENRA
ENRA is the ICAO airport code for Mo i Rana Airport, Røssvoll in Norway.
-
D.
ANLE
ANLE is the North American Academy of the Spanish Language, an institution dedicated to studying, preserving, and promoting the correct use of Spanish in the United States.
-
E.
ENH
ENH is the IATA airport code for Enshi Xujiaping Airport, a regional airport serving Enshi in Hubei Province, China.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e0414877d88190804ee76566004e13 |
completed | April 16, 2026, 1:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d5e82a48190bb0a10ebc2412129 |
completed | May 9, 2026, 1:57 p.m. |
| NEDg | Description generation | batch_69ff3ea7d5ac81908bd1ee64de39dba7 |
completed | May 9, 2026, 2:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff413a68488190a6c8907e36a602dc |
completed | May 9, 2026, 2:14 p.m. |
Created at: April 10, 2026, 4:06 a.m.