Triple
T29421693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helsinki City Ferry to Suomenlinna |
E746171
|
entity |
| Predicate | hasBoardingFor |
P33919
|
FINISHED |
| Object | pedestrians |
—
|
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: pedestrians | Statement: [Helsinki City Ferry to Suomenlinna, hasBoardingFor, pedestrians]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBoardingFor Context triple: [Helsinki City Ferry to Suomenlinna, hasBoardingFor, pedestrians]
-
A.
hasBoardingType
Indicates the specific manner or method by which an entity is boarded or accessed (e.g., how passengers or items are taken on).
-
B.
hasBoardingAreaFor
chosen
Indicates that one entity provides or contains a designated area where passengers can board another entity (such as a vehicle or vessel).
-
C.
hasBoardingOption
Indicates that an entity offers or is associated with a particular way or method by which passengers or items can board or be taken on.
-
D.
isBoarding
Indicates that an entity is in the process of getting onto or entering a vehicle, vessel, or similar mode of transport.
-
E.
boardingFor
Indicates that one entity serves as the designated boarding location or facility for another entity, such as passengers or animals.
- 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_69f0a79f6d5c8190a350baed0157e06f |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
Created at: April 28, 2026, 3:06 p.m.