Triple
T3674886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CYYZ |
E77966
|
entity |
| Predicate | isLargestAirportInCountryBy |
P296
|
FINISHED |
| Object | passenger traffic |
—
|
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: passenger traffic | Statement: [CYYZ, isLargestAirportInCountryBy, passenger traffic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isLargestAirportInCountryBy Context triple: [CYYZ, isLargestAirportInCountryBy, passenger traffic]
-
A.
largestAirport
chosen
Indicates that one airport is the largest (typically by area, traffic, or capacity) among a specified set or within a given region.
-
B.
hasInternationalAirport
Indicates that a place possesses an airport that handles international flights and services cross-border air traffic.
-
C.
isOldestInternationalAirportInOperationIn
Indicates that an airport is the oldest international airport still in operation within a specified geographic area or jurisdiction.
-
D.
hasMajorAirport
Indicates that a location possesses at least one significant airport that serves as a primary hub for air travel in that area.
-
E.
hasLongestRunwayIn
Indicates that an entity possesses the runway of greatest length within a specified location or region.
- F. None of above.
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_69ad85e083008190b2e1b7085fe500bd |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc4619cf08190a09a4a820c59cbc4 |
completed | March 8, 2026, 6:48 p.m. |
| PD | Predicate disambiguation | batch_69adb84a20288190a092e4a1b045fe3f |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:25 p.m.