Triple
T1180132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canadian Airlines |
E25115
|
entity |
| Predicate | servedDestinationCountAtPeak |
P13065
|
FINISHED |
| Object | over 160 destinations |
—
|
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: over 160 destinations | Statement: [Canadian Airlines, servedDestinationCountAtPeak, over 160 destinations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedDestinationCountAtPeak Context triple: [Canadian Airlines, servedDestinationCountAtPeak, over 160 destinations]
-
A.
servesDestinationCount
chosen
Indicates the number of distinct destinations that an entity (such as a service, route, or provider) serves.
-
B.
circulationPeak
Indicates the highest level or maximum point reached in the circulation of something (such as money, media, or resources) within a given period or system.
-
C.
peakDayAttendance
Indicates the number of attendees present on the single highest-attendance day within a given period or event.
-
D.
memberCountAtPeak
Indicates the highest number of members that an entity (such as a group or organization) has had at any point in time.
-
E.
numberOfFloorsServed
Indicates the total count of distinct floors that are served or accessed by a given entity (such as an elevator or service system).
- 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_69a494267b4c819088c97a59182bf56a |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd53e4b48190abb2167f8074a6bc |
completed | March 1, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5844348190b01ac6506906ba3b |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.