Triple
T1691585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Air Europa |
E36560
|
entity |
| Predicate | ICAOcode |
P419
|
FINISHED |
| Object | AEA |
E56664
|
NE FINISHED |
How this triple was built (2 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: AEA | Statement: [Air Europa, ICAOcode, AEA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AEA Context triple: [Air Europa, ICAOcode, AEA]
-
A.
AEA
chosen
AEA is a major professional organization of economists in the United States that publishes leading academic journals and promotes economic research and education.
-
B.
ANA
ANA is the standard three-letter abbreviation used for the Anaheim Ducks, a professional ice hockey team in the National Hockey League.
-
C.
ANA
ANA is the commonly used abbreviation for the Afghan National Army, the former main land warfare branch of Afghanistan’s armed forces.
-
D.
URA
URA (Universities Research Association) is a consortium of research universities that collaborates to advance high-energy physics and other scientific research through managing and supporting major research facilities and projects.
-
E.
ACA
ACA is the common abbreviation for the Affordable Care Act, a major U.S. health care reform law enacted in 2010 to expand insurance coverage and consumer protections.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a886151508819084fa7f1ce6e05577 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa6298fa748190acabb9f1d42bd3f5 |
completed | March 6, 2026, 5:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad79947c908190b807205bd44c3254 |
completed | March 8, 2026, 1:28 p.m. |
Created at: March 4, 2026, 7:29 p.m.