Triple
T10950665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamburg Airport |
E258716
|
entity |
| Predicate | has code |
P24101
|
FINISHED |
| Object | EDDH |
E258717
|
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: EDDH | Statement: [Hamburg Airport, has code, EDDH]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: EDDH Context triple: [Hamburg Airport, has code, EDDH]
-
A.
EDDH
chosen
EDDH is the ICAO airport code for Hamburg Airport, a major international airport in northern Germany.
-
B.
EDDM
EDDM is the ICAO airport code for Munich Airport, a major international aviation hub in Germany.
-
C.
EDDS
EDDS is the ICAO airport code designating Stuttgart Airport in Germany.
-
D.
EDDT
EDDT is the ICAO airport code for Berlin Tegel Airport, the former main international airport of Berlin, Germany.
-
E.
EDD
EDD is the California state agency responsible for administering unemployment insurance, disability insurance, paid family leave, and various workforce and labor market programs.
- 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_69d6aa88500c819097d7032ca578e74f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770ed2f1c819081ec58457f57889d |
completed | April 9, 2026, 9:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2d733f7d88190b45df5c155ff5a46 |
completed | April 18, 2026, 12:58 a.m. |
Created at: April 8, 2026, 9:23 p.m.