Triple
T18975016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CYHZ |
E464271
|
entity |
| Predicate | regionRankByTraffic |
P134010
|
FINISHED |
| Object | one of the busiest airports in Atlantic Canada |
—
|
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: one of the busiest airports in Atlantic Canada | Statement: [CYHZ, regionRankByTraffic, one of the busiest airports in Atlantic Canada]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionRankByTraffic Context triple: [CYHZ, regionRankByTraffic, one of the busiest airports in Atlantic Canada]
-
A.
rankingInCountryByTraffic
Indicates the position of something in an ordered list of entities within a specific country, based on the amount of traffic it receives.
-
B.
countryRanking
Indicates the relative position or rank assigned to a country within a specific ordered list or comparative evaluation.
-
C.
populationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
D.
passengerTrafficRankingWorld
Indicates the relative position of an entity in a global ranking based on the volume of passenger traffic it handles.
-
E.
countryRankingContext
Indicates the contextual framework or criteria under which a country's ranking is determined or interpreted.
- 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_69d8dd008af48190a97ff1c6488edf1b |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d61e71988190817cada25672a1ce |
completed | April 20, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69e4a2f437648190b85650dae8885d48 |
completed | April 19, 2026, 9:40 a.m. |
| PDg | Predicate description generation | batch_69e4ad8e075c8190ad561edc5e520057 |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, noon