Triple
T1885556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aeroparque Jorge Newbery |
E39955
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object |
AEP
AEP is the IATA airport code for Aeroparque Jorge Newbery, the main domestic and regional airport serving Buenos Aires, Argentina.
|
E209570
|
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: AEP | Statement: [Aeroparque Jorge Newbery, IATAcode, AEP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AEP Context triple: [Aeroparque Jorge Newbery, IATAcode, AEP]
-
A.
AET
AET is the former stock ticker symbol for Aetna Inc., a major U.S. health insurance and managed care company.
-
B.
ANEP
ANEP is Uruguay’s National Administration of Public Education, the autonomous body responsible for overseeing and managing the country’s public education system.
-
C.
AEC
AEC was the common abbreviation for the United States Atomic Energy Commission, the federal agency that oversaw nuclear energy development and regulation in the mid-20th century.
-
D.
AEC
AEC is a European network and advocacy organization representing higher music education institutions such as conservatoires, academies, and music universities.
-
E.
AEC
AEC is a regional economic integration initiative among ASEAN member states aimed at creating a single market and production base to enhance competitiveness and economic growth in Southeast Asia.
- 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: AEP Triple: [Aeroparque Jorge Newbery, IATAcode, AEP]
Generated description
AEP is the IATA airport code for Aeroparque Jorge Newbery, the main domestic and regional airport serving Buenos Aires, Argentina.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AEP Target entity description: AEP is the IATA airport code for Aeroparque Jorge Newbery, the main domestic and regional airport serving Buenos Aires, Argentina.
-
A.
AET
AET is the former stock ticker symbol for Aetna Inc., a major U.S. health insurance and managed care company.
-
B.
ANEP
ANEP is Uruguay’s National Administration of Public Education, the autonomous body responsible for overseeing and managing the country’s public education system.
-
C.
AEC
AEC was the common abbreviation for the United States Atomic Energy Commission, the federal agency that oversaw nuclear energy development and regulation in the mid-20th century.
-
D.
AEC
AEC is a European network and advocacy organization representing higher music education institutions such as conservatoires, academies, and music universities.
-
E.
AEC
AEC is a regional economic integration initiative among ASEAN member states aimed at creating a single market and production base to enhance competitiveness and economic growth in Southeast Asia.
- 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_69a88633e4fc8190b7eb40463e048ec5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb11eb2d0819088d67b1cfc772049 |
completed | March 7, 2026, 5:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69addf61413081909c0e840590aaf631 |
completed | March 8, 2026, 8:43 p.m. |
| NEDg | Description generation | batch_69addfcecdf48190a325eb5c8b10f238 |
completed | March 8, 2026, 8:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ade0ba34ac8190ac94f7dbb5778f70 |
completed | March 8, 2026, 8:48 p.m. |
Created at: March 4, 2026, 7:34 p.m.