Triple
T16575627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liverpool Cruise Terminal |
E402700
|
entity |
| Predicate | hasCoachDropOffArea |
P24210
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Liverpool Cruise Terminal, hasCoachDropOffArea, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoachDropOffArea Context triple: [Liverpool Cruise Terminal, hasCoachDropOffArea, yes]
-
A.
hasDropOffArea
chosen
Indicates that an entity provides a designated area where items, passengers, or goods can be temporarily left or unloaded.
-
B.
hasStopArea
Indicates that an entity is associated with or contains a specific stop area, such as a designated location where vehicles stop.
-
C.
hasStandingArea
Indicates that an entity includes or provides a designated area where people can stand.
-
D.
hasParkingFor
Indicates that a place or facility provides designated parking spaces suitable for a specified type of vehicle or user.
-
E.
hasPedestrianArea
Indicates that a location or zone includes a designated area intended for pedestrian use only or primarily.
- 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.