Triple
T28853412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | historic county of Bute |
E728665
|
entity |
| Predicate | hasHistoricTransportLink |
P192563
|
FINISHED |
| Object | Clyde steamer services |
—
|
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: Clyde steamer services | Statement: [historic county of Bute, hasHistoricTransportLink, Clyde steamer services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricTransportLink Context triple: [historic county of Bute, hasHistoricTransportLink, Clyde steamer services]
-
A.
isOnHistoricTransportCorridor
Indicates that something is located along or within a transportation route that has recognized historical significance.
-
B.
hasTramHistory
Indicates that there exists a historical association or record of tram-related activity or infrastructure involving the subject.
-
C.
hasRailwayJunctionHistorically
Indicates that an entity historically functioned as a railway junction, where multiple rail lines intersected or connected in the past.
-
D.
hasTransportHistoryAs
Indicates that an entity has a record or log of being transported, characterized or classified in a specific way.
-
E.
hasGoodTransportLinks
Indicates that a place is well connected to other locations by efficient and convenient transport options.
- F. None of above. chosen
Provenance (4 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_69f0319f4e5481909e4c439dbe8be940 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69fd19f791f48190bbb6f6047f9ddc59 |
completed | May 7, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69fd0df365948190bc9bfc7ffd46acd8 |
completed | May 7, 2026, 10:10 p.m. |
| PDg | Predicate description generation | batch_69fd19f6a7888190aa7eee2b87687c53 |
completed | May 7, 2026, 11:02 p.m. |
Created at: April 28, 2026, 6:44 a.m.