Triple
T9963859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great North of Scotland Railway |
E195631
|
entity |
| Predicate | servedRoyalResidence |
P91692
|
FINISHED |
| Object | Balmoral Castle via Ballater |
—
|
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: Balmoral Castle via Ballater | Statement: [Great North of Scotland Railway, servedRoyalResidence, Balmoral Castle via Ballater]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedRoyalResidence Context triple: [Great North of Scotland Railway, servedRoyalResidence, Balmoral Castle via Ballater]
-
A.
becameRoyalResidenceIn
Indicates that a place or building started serving as an official royal residence at a specified point in time.
-
B.
containsRoyalResidence
Indicates that a location includes or encompasses a residence used by royalty.
-
C.
monarchUsedAsResidence
Indicates that a monarch uses or has used a particular place as their residence.
-
D.
servedAsImperialResidenceFrom
Indicates that an entity functioned as an imperial residence starting from a specified point in time.
-
E.
usedAsRoyalResidenceUntil
Indicates that something served as a royal residence up to a specified point in time.
- 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_69ca82ebd1288190912f9e4482d1fa35 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb71a33b48190a18c1a9023f249d2 |
completed | April 2, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9ae19c819099fb3635e57c79be |
completed | April 1, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69cd36f112bc81908b473787e702de2f |
completed | April 1, 2026, 3:17 p.m. |
Created at: March 30, 2026, 8:47 p.m.