Triple
T22210402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asaba International Airport |
E548928
|
entity |
| Predicate | hasICAOCode |
P419
|
FINISHED |
| Object |
DNAS
DNAS is the ICAO airport code assigned to Asaba International Airport in Delta State, Nigeria.
|
E1524085
|
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: DNAS | Statement: [Asaba International Airport, hasICAOCode, DNAS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DNAS Context triple: [Asaba International Airport, hasICAOCode, DNAS]
-
A.
DNK
DNK is the IATA airport code for Dnipro International Airport, a commercial airport serving the city of Dnipro in Ukraine.
-
B.
DNKA
DNKA is the ICAO airport code for Kaduna International Airport in Kaduna, Nigeria.
-
C.
ODNA
ODNA is the acronym for the Office of the Director of Net Assessment, a U.S. Department of Defense office responsible for long-term strategic military assessments and competitive analysis.
-
D.
DNAA
DNAA is the ICAO airport code for Nnamdi Azikiwe International Airport, the main international gateway serving Abuja, Nigeria’s capital city.
-
E.
CDNA
CDNA is AMD’s GPU architecture family optimized for high-performance computing and data center workloads, emphasizing compute efficiency over traditional graphics features.
- 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: DNAS Triple: [Asaba International Airport, hasICAOCode, DNAS]
Generated description
DNAS is the ICAO airport code assigned to Asaba International Airport in Delta State, Nigeria.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DNAS Target entity description: DNAS is the ICAO airport code assigned to Asaba International Airport in Delta State, Nigeria.
-
A.
DNK
DNK is the IATA airport code for Dnipro International Airport, a commercial airport serving the city of Dnipro in Ukraine.
-
B.
DNKA
DNKA is the ICAO airport code for Kaduna International Airport in Kaduna, Nigeria.
-
C.
ODNA
ODNA is the acronym for the Office of the Director of Net Assessment, a U.S. Department of Defense office responsible for long-term strategic military assessments and competitive analysis.
-
D.
DNAA
DNAA is the ICAO airport code for Nnamdi Azikiwe International Airport, the main international gateway serving Abuja, Nigeria’s capital city.
-
E.
CDNA
CDNA is AMD’s GPU architecture family optimized for high-performance computing and data center workloads, emphasizing compute efficiency over traditional graphics features.
- 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_69e11e3f7e04819089806d81d5ac431e |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12b2bcf748190a9721f0c9ae17e70 |
completed | April 28, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0aa61cc9e48190ba5f6eb2a7cf3c9b |
completed | May 18, 2026, 5:39 a.m. |
| NEDg | Description generation | batch_6a0aa6c001d48190b49866f02514aa28 |
completed | May 18, 2026, 5:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0aa74204a081909fa0d80858bfa6bb |
completed | May 18, 2026, 5:44 a.m. |
Created at: April 16, 2026, 8:36 p.m.