Triple
T16575642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liverpool Cruise Terminal |
E402700
|
entity |
| Predicate | hasCruiseCallsPerYear |
P61060
|
FINISHED |
| Object | dozens of cruise calls per season |
—
|
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: dozens of cruise calls per season | Statement: [Liverpool Cruise Terminal, hasCruiseCallsPerYear, dozens of cruise calls per season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCruiseCallsPerYear Context triple: [Liverpool Cruise Terminal, hasCruiseCallsPerYear, dozens of cruise calls per season]
-
A.
hasCruiseTraffic
chosen
Indicates that there is cruise ship traffic occurring at or involving a particular location or route.
-
B.
cruiseCapability
Indicates the ability of an entity to travel or operate in a steady, sustained cruising mode under its own power.
-
C.
servesCruisePort
Indicates that one entity (typically a transportation service or route) provides service to or operates at a particular cruise port.
-
D.
hasFestivalFrequency
Indicates how often a festival or recurring celebratory event takes place within a given time period.
-
E.
hasTour
Indicates that an entity offers, includes, or is associated with a tour experience or guided visit.
- 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.