Triple
T34385407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upper Barrakka Lift |
E882542
|
entity |
| Predicate | capacityPerCabin |
P179149
|
FINISHED |
| Object | around 21 persons |
—
|
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: around 21 persons | Statement: [Upper Barrakka Lift, capacityPerCabin, around 21 persons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capacityPerCabin Context triple: [Upper Barrakka Lift, capacityPerCabin, around 21 persons]
-
A.
cabinVolumeCubicMeters
Indicates the volume of an enclosed cabin space measured in cubic meters.
-
B.
cabinConfiguration
Indicates how the interior space of a vehicle, vessel, or aircraft is arranged and organized for occupants or cargo.
-
C.
passengerCapacityCategory
Indicates the classification of an entity based on the number of passengers it is designed or allowed to carry.
-
D.
sleepingCapacity
Indicates the maximum number of people or occupants that can sleep in or be accommodated for sleeping by something.
-
E.
crewAndPassengersCount
Indicates the total number of people on a vehicle or vessel, combining both crew members and passengers.
- 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_69f349c0219881909393bbbc1edc8161 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71c35327c8190884f1bfe12bd2cd7 |
completed | May 3, 2026, 9:58 a.m. |
| PD | Predicate disambiguation | batch_69f71822d0e88190ac9731c7ae5a4def |
completed | May 3, 2026, 9:40 a.m. |
| PDg | Predicate description generation | batch_69f71c33edac8190a59f6ff19b265fc5 |
completed | May 3, 2026, 9:58 a.m. |
Created at: May 1, 2026, 1:59 a.m.