Triple
T38688506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port Pendennis Marina |
E949190
|
entity |
| Predicate | hasBerthingType |
P35993
|
FINISHED |
| Object | sheltered berths |
—
|
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: sheltered berths | Statement: [Port Pendennis Marina, hasBerthingType, sheltered berths]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBerthingType Context triple: [Port Pendennis Marina, hasBerthingType, sheltered berths]
-
A.
berthType
chosen
Indicates the specific kind or category of berth associated with an entity, such as the type of sleeping or docking space provided.
-
B.
hasBerths
Indicates that one entity provides or contains sleeping or docking berths for another entity.
-
C.
hasBerthLength
Indicates the length of a berth allocated to or associated with an entity.
-
D.
mooringType
Indicates the specific method or system by which a vessel or floating structure is secured in place.
-
E.
berthingOrDockingTarget
Indicates that an entity serves as the location or structure where a vessel or vehicle is intended to berth or dock.
- 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_69f76efe16148190befd5dd59c3dfeaa |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd6dbd1b648190b1a0b391c03aebc5 |
completed | May 8, 2026, 4:59 a.m. |
| PD | Predicate disambiguation | batch_69fd6a9020548190bbfa845360ac85fb |
completed | May 8, 2026, 4:46 a.m. |
Created at: May 3, 2026, 4:33 p.m.