Triple
T38515933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Gijón |
E922341
|
entity |
| Predicate | hasHarbourBasin |
P44134
|
FINISHED |
| Object | commercial harbour basin |
—
|
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: commercial harbour basin | Statement: [Port of Gijón, hasHarbourBasin, commercial harbour basin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHarbourBasin Context triple: [Port of Gijón, hasHarbourBasin, commercial harbour basin]
-
A.
hasHarbor
Indicates that a place possesses or contains a harbor for docking or sheltering vessels.
-
B.
hasHarbourEntrance
Indicates that an entity serves as the entrance or access point to a harbour for another entity.
-
C.
harborBasinName
Indicates the name assigned to a specific harbor basin within a port or harbor area.
-
D.
hasHarborCity
Indicates that one entity possesses or is associated with a city that functions as its harbor or port.
-
E.
hasHarborFeature
chosen
Indicates that something possesses or includes a specific harbor-related characteristic, structure, or facility.
- 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_69f76ea5f5588190bd0b28c82e975640 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcdaa36f90819093f8661969990c7d |
completed | May 7, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fefc588190b063d7ea1ec87b07 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:32 p.m.