Triple
T33006547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fenella |
E844515
|
entity |
| Predicate | passengerCapability |
P180566
|
FINISHED |
| Object | passenger transport |
—
|
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 transport | Statement: [Fenella, passengerCapability, passenger transport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: passengerCapability Context triple: [Fenella, passengerCapability, passenger transport]
-
A.
passengerCondition
Indicates the state or status of a passenger, such as their health, comfort, or special needs, in relation to a trip or transport situation.
-
B.
hasPassengerAmenity
Indicates that an entity provides or is equipped with a specific amenity intended for the comfort or convenience of its passengers.
-
C.
appliesToPassengerType
Indicates that a rule, condition, or attribute is relevant or restricted to a specific type or category of passenger.
-
D.
passengerCapacityCategory
Indicates the classification of an entity based on the number of passengers it is designed or allowed to carry.
-
E.
hasCrewCapacity
Indicates that an entity is capable of accommodating a specified number of crew members.
- 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_69f3494e59f08190b9127c693e5c7e8f |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69f7431aac148190bb6aac59817c174a |
completed | May 3, 2026, 12:44 p.m. |
Created at: May 1, 2026, 1:23 a.m.