Triple
T12384954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donald I of Scotland |
E295838
|
entity |
| Predicate | monarchOf |
P765
|
FINISHED |
| Object | Alba |
E175945
|
NE 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: Alba | Statement: [Donald I of Scotland, monarchOf, Alba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alba Context triple: [Donald I of Scotland, monarchOf, Alba]
-
A.
Alba
chosen
Alba is the Gaelic name for the early medieval kingdom that evolved into the nation of Scotland.
-
B.
Alba
Alba is a prominent Spanish noble house historically associated with the powerful Dukes of Alba.
-
C.
Alba
Alba is a historic town in Italy’s Piedmont region, renowned for its white truffles, fine wines, and medieval architecture.
-
D.
El Alba
El Alba is the popular nickname of the Spanish football club Albacete Balompié, which is based in the city of Albacete and traditionally plays in white.
-
E.
Alba Regia
Alba Regia is the historical Latin name of the Hungarian city of Székesfehérvár, a former royal seat and coronation site.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fbc3f608190b0ee3c4f304a94db |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6347816408190904ea71d2a72398f |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:54 p.m.