Triple
T14783062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Helsingborg |
E347439
|
entity |
| Predicate | nearbyStraitCrossingType |
P10712
|
FINISHED |
| Object | short-sea ferry route |
—
|
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: short-sea ferry route | Statement: [Port of Helsingborg, nearbyStraitCrossingType, short-sea ferry route]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyStraitCrossingType Context triple: [Port of Helsingborg, nearbyStraitCrossingType, short-sea ferry route]
-
A.
nearbyStrait
Indicates that one entity is located close to or adjacent to a particular strait.
-
B.
hasBridgeCrossings
Indicates that one entity has one or more bridge structures that span across or connect over another entity (such as a road, river, or area).
-
C.
hasBridgeTypeCrossing
Indicates that a bridge is characterized by a specific type of crossing it provides or supports.
-
D.
crossingType
chosen
Indicates the specific kind or category of crossing (e.g., how or where one thing passes over, through, or across another).
-
E.
waterwayTypeCrossed
Indicates the specific kind of waterway (e.g., river, canal, stream) that is being crossed in the described relationship or action.
- 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deca9de3f48190b7706925e2947cf5 |
completed | April 14, 2026, 11:15 p.m. |
| PD | Predicate disambiguation | batch_69de8c090d1081909b5a9bf437499d6c |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:31 a.m.