Triple
T16575610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liverpool Cruise Terminal |
E402700
|
entity |
| Predicate | hasFloatingPontoonLength |
P62876
|
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, hasFloatingPontoonLength, 350 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFloatingPontoonLength Context triple: [Liverpool Cruise Terminal, hasFloatingPontoonLength, 350 metres]
-
A.
shipLength
Indicates the physical length measurement of a ship.
-
B.
hasShoreLengthOn
Indicates that an entity has a specified length of shoreline along or bordering another geographic feature (such as a body of water or coast).
-
C.
numberOfBoatsWidth
Indicates the count of boats arranged or present across the width of a given area or span.
-
D.
hasPierLength
chosen
Indicates that one entity (typically a pier or similar structure) has a specified length measurement.
-
E.
hasBoatCapacity
Indicates the maximum number of people or amount of load that a boat is designed or allowed to carry.
- 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_69e296a47b7481909d9958158510c806 |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:16 a.m.