Triple
T26747167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Straumsnes Station |
E674431
|
entity |
| Predicate | lineFunction |
P76380
|
FINISHED |
| Object | freight transport |
—
|
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: freight transport | Statement: [Straumsnes Station, lineFunction, freight transport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lineFunction Context triple: [Straumsnes Station, lineFunction, freight transport]
-
A.
lineElement
Indicates a relationship where something functions as, or is identified as, an element or segment of a line within a larger linear structure or representation.
-
B.
lineExample
Indicates that one entity serves as an illustrative or representative example of a particular line, sequence, or linear construct associated with another entity.
-
C.
lineUse
chosen
Indicates how a particular line (such as a route, track, or service line) is utilized or purposed within a system or network.
-
D.
loopLine
Indicates that a line or path forms a closed loop, returning to its starting point without interruption.
-
E.
lineType
Indicates the specific category or style of a line used in a representation, such as its function or visual convention.
- 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_69eecda63a3881908095c47900692e65 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f6188630dc8190ba0602ebe2b3ab6b |
completed | May 2, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69f60b8dfa0c8190864e1a940024d0a0 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 27, 2026, 3:52 a.m.