Triple
T38125880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Canada (2007) |
E952068
|
entity |
| Predicate | hasPassengerMarket |
P202341
|
FINISHED |
| Object | international passengers |
—
|
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: international passengers | Statement: [SS Empress of Canada (2007), hasPassengerMarket, international passengers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerMarket Context triple: [SS Empress of Canada (2007), hasPassengerMarket, international passengers]
-
A.
hasPassengerOperator
Indicates that an entity (such as a vehicle or service) is operated by an organization or person responsible for carrying passengers.
-
B.
hasPassengerTrafficFrom
Indicates that an entity receives or handles passenger traffic originating from another entity.
-
C.
hasPassengerHandling
Indicates that an entity is responsible for or involved in managing the processes and services related to handling passengers.
-
D.
hasPassengerAirlineService
Indicates that a location or facility is served by scheduled passenger airline flights.
-
E.
belongsToAviationMarket
Indicates that something is part of, or associated with, the aviation industry market segment.
- 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_69f76f083548819082bd2bbf53c79e8e |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a007338002081908cb6340d65ff86d5 |
completed | May 10, 2026, 11:59 a.m. |
| PD | Predicate disambiguation | batch_6a0072a137ac8190a7debeb28e738e03 |
completed | May 10, 2026, 11:57 a.m. |
| PDg | Predicate description generation | batch_6a00733756848190b94524b42d6edf0a |
completed | May 10, 2026, 11:59 a.m. |
Created at: May 3, 2026, 4:21 p.m.