Triple
T3381757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin Brandenburg Airport |
E71200
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | BER |
E71200
|
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: BER | Statement: [Berlin Brandenburg Airport, shortName, BER]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BER Context triple: [Berlin Brandenburg Airport, shortName, BER]
-
A.
BER
chosen
BER is Berlin Brandenburg Airport, the main international airport serving Germany’s capital region.
-
B.
BEL
BEL is the ICAO airline designator used to identify Brussels Airlines in international aviation operations.
-
C.
BEL
BEL is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies Belgium in international standards and data systems.
-
D.
BUR
BUR is the three-letter IATA airport code for Hollywood Burbank Airport, a commercial airport serving the Los Angeles area in Southern California.
-
E.
BE
BE is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Belgium in international standards and systems.
- 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_69ad85a8fd9c819095ecedf838d2bf1b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb5e9af608190bfb228ef99a87bb7 |
completed | March 8, 2026, 5:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b34bc3f13c81909bec375bd080b7f3 |
completed | March 12, 2026, 11:27 p.m. |
Created at: March 8, 2026, 3:14 p.m.