Triple
T4741877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drammen |
E105261
|
entity |
| Predicate | portSpecialization |
P30457
|
FINISHED |
| Object | car imports |
—
|
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: car imports | Statement: [Drammen, portSpecialization, car imports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portSpecialization Context triple: [Drammen, portSpecialization, car imports]
-
A.
hasPortSpecialization
chosen
Indicates that an entity has a specific functional or technical specialization related to a port or interface.
-
B.
positionSpecialization
Indicates that one position is a more specialized or focused variant of another, broader position.
-
C.
portConfiguration
Indicates how ports are arranged, assigned, or set up for use within a system or device.
-
D.
portLocation
Indicates that a port is geographically situated at or associated with a specific location.
-
E.
port
Indicates a relationship where one entity serves as a harbor, access point, or interface through which another entity can enter, exit, or connect.
- 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_69bd43ef87a48190a5bc3600711aa032 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64a7153881909eac451fc7566d25 |
completed | March 20, 2026, 3:15 p.m. |
| PD | Predicate disambiguation | batch_69bd6221c3b881908604f35f8de6f16b |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:19 p.m.