Triple
T16575619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liverpool Cruise Terminal |
E402700
|
entity |
| Predicate | hasCarParkingCapacity |
P21999
|
FINISHED |
| Object | approx 300 spaces |
—
|
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: approx 300 spaces | Statement: [Liverpool Cruise Terminal, hasCarParkingCapacity, approx 300 spaces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCarParkingCapacity Context triple: [Liverpool Cruise Terminal, hasCarParkingCapacity, approx 300 spaces]
-
A.
hasParking
Indicates that a place or facility provides designated parking space(s) available for use.
-
B.
hasParkingFor
Indicates that a place or facility provides designated parking spaces suitable for a specified type of vehicle or user.
-
C.
hasUndergroundParking
Indicates that a place or building provides parking facilities located below ground level.
-
D.
numberOfParkingSpaces
chosen
Indicates the total count of parking spaces associated with a particular entity or location.
-
E.
hasParkingNearby
Indicates that a location has one or more parking facilities or spaces available within a close surrounding area.
- 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_69d88387363c8190a97a0c942130de97 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3595cb65481909be62a52deff3d44 |
completed | April 18, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69e296a7d9d0819088555bca6c936e79 |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:16 a.m.