Triple
T17674034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EDDF |
E440598
|
entity |
| Predicate | hasPassengerTrafficRankInGermany |
P128500
|
FINISHED |
| Object | 1 |
—
|
LITERAL 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: 1 | Statement: [EDDF, hasPassengerTrafficRankInGermany, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerTrafficRankInGermany Context triple: [EDDF, hasPassengerTrafficRankInGermany, 1]
-
A.
hasPassengerTrafficRank
Indicates the relative position or ranking of an entity based on the volume of passenger traffic it handles compared to others.
-
B.
passengerTrafficRankInEurope
Indicates the relative position of an entity in Europe based on the volume of passenger traffic it handles.
-
C.
peakPassengerTrafficRank
Indicates the relative position of an entity in an ordered list based on the amount of passenger traffic it experiences at its peak.
-
D.
cargoTrafficRankInEurope
Indicates the relative position of an entity in terms of cargo traffic volume compared to other entities within Europe.
-
E.
passengerTrafficRankingWorld
Indicates the relative position of an entity in a global ranking based on the volume of passenger traffic it handles.
- F. None of above. chosen
Provenance (4 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46f6ba22081909e2099490c047378 |
completed | April 19, 2026, 6 a.m. |
| PD | Predicate disambiguation | batch_69e3cde007d8819090dd92eea9f022cc |
completed | April 18, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69e3cfaac2b881909e1140339eb1a0dd |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 10 a.m.