Triple
T16575609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liverpool Cruise Terminal |
E402700
|
entity |
| Predicate | hasBerthLength |
P123373
|
FINISHED |
| Object | 350 metres |
—
|
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: 350 metres | Statement: [Liverpool Cruise Terminal, hasBerthLength, 350 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBerthLength Context triple: [Liverpool Cruise Terminal, hasBerthLength, 350 metres]
-
A.
hasBerthDepth
Indicates the depth of water available at a specific berth where a vessel can be moored.
-
B.
hasBerths
Indicates that one entity provides or contains sleeping or docking berths for another entity.
-
C.
hasPierLength
Indicates that one entity (typically a pier or similar structure) has a specified length measurement.
-
D.
numberOfBerths
Indicates the quantity of berths (sleeping places or docking spaces) associated with an entity.
-
E.
berthType
Indicates the specific kind or category of berth associated with an entity, such as the type of sleeping or docking space provided.
- 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_69e296a47b7481909d9958158510c806 |
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.