Triple
T16575618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liverpool Cruise Terminal |
E402700
|
entity |
| Predicate | hasBaggageXrayMachines |
P123374
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Liverpool Cruise Terminal, hasBaggageXrayMachines, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBaggageXrayMachines Context triple: [Liverpool Cruise Terminal, hasBaggageXrayMachines, 2]
-
A.
hasBaggageCheck
Indicates that an entity provides or is associated with a service or facility for checking in baggage.
-
B.
hasBaggageSystem
Indicates that an entity is equipped with or utilizes a baggage handling system.
-
C.
hasBaggageClaim
Indicates that a location, typically a transportation hub, includes or provides a baggage claim area for retrieving luggage.
-
D.
hasLuggage
Indicates that an entity is carrying, possessing, or associated with one or more pieces of luggage.
-
E.
hasCheckedBaggage
Indicates that an entity is associated with baggage that has been checked in for transport, typically for a trip or flight.
- 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_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. |
| PDg | Predicate description generation | batch_69e2d7fb02f481908885a226c2191231 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:16 a.m.