Triple
T7622114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cape Liberty Cruise Port |
E172520
|
entity |
| Predicate | hasNumberOfBerths |
P31355
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Cape Liberty Cruise Port, hasNumberOfBerths, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfBerths Context triple: [Cape Liberty Cruise Port, hasNumberOfBerths, 1]
-
A.
hasBerths
Indicates that one entity provides or contains sleeping or docking berths for another entity.
-
B.
hasNumberOfFerrySlips
chosen
Indicates the specific count of ferry slips associated with or available at a given entity.
-
C.
berthType
Indicates the specific kind or category of berth associated with an entity, such as the type of sleeping or docking space provided.
-
D.
hasBerthDepth
Indicates the depth of water available at a specific berth where a vessel can be moored.
-
E.
wildCardBerthsCount
Indicates the number of wildcard berths (extra or non-standard qualification spots) allocated in a competition or selection process.
- 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_69c699506b308190826894dab1d9ea86 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fe73ff7c8190ab1218d97b37416d |
completed | March 27, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e725a88190b1f05dd224f7f4f2 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:56 p.m.