Triple
T31147758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berendrecht |
E793976
|
entity |
| Predicate | hasPortInfrastructureNearby |
P124983
|
FINISHED |
| Object | Port of Antwerp |
—
|
NE NERFINISHED |
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: Port of Antwerp | Statement: [Berendrecht, hasPortInfrastructureNearby, Port of Antwerp]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPortInfrastructureNearby Context triple: [Berendrecht, hasPortInfrastructureNearby, Port of Antwerp]
-
A.
hasNearbyInfrastructureType
chosen
Indicates that an entity is located close to infrastructure of a specified type.
-
B.
hasNearbyWaterInfrastructure
Indicates that a location or entity is situated close to water-related infrastructure such as pipes, treatment facilities, or distribution systems.
-
C.
hasOutletNear
Indicates that one entity has a physical outlet or branch located in close proximity to another specified location or entity.
-
D.
hasStationNear
Indicates that one entity has a station located in close proximity to another entity.
-
E.
hasPublicTransitInfrastructure
Indicates that a location or area is equipped with facilities and systems that support public transportation services (e.g., buses, trains, trams).
- 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_69f224d41bb48190a5621cd1485e3a30 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe30bc64308190b603ff1b30c2aeee |
completed | May 8, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fe2f7175b081908dd61e1513620bbe |
completed | May 8, 2026, 6:46 p.m. |
Created at: April 29, 2026, 9:06 p.m.