Triple
T4160037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ala 48 |
E91508
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | Ala 48 |
E91508
|
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: Ala 48 | Statement: [Ala 48, hasAbbreviation, Ala 48]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ala 48 Context triple: [Ala 48, hasAbbreviation, Ala 48]
-
A.
Ala 48
chosen
Ala 48 is a wing of the Spanish Air Force responsible for operating transport and support aircraft in national and international missions.
-
B.
Ala 49
Ala 49 is a unit of the Spanish Air Force, likely an air wing responsible for operating and supporting specific aircraft and missions within Spain’s military aviation structure.
-
C.
Ala 14
Ala 14 is a fighter wing of the Spanish Air Force known for operating advanced combat aircraft in air defense and tactical missions.
-
D.
Ala 31
Ala 31 is a transport wing of the Spanish Air Force, primarily responsible for strategic and tactical airlift missions.
-
E.
Ala 78
Ala 78 is a training wing of the Spanish Air Force specializing in helicopter pilot instruction and related aviation training.
- 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_69aed9626ebc8190a39de631788bea3e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af029454d08190b7ff32776081fabc |
completed | March 9, 2026, 5:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f40678481908894ff315932a610 |
completed | March 14, 2026, 3:31 p.m. |
Created at: March 9, 2026, 3:44 p.m.