Triple
T22162781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dun Caan |
E547712
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Raasay |
—
|
NE NERFINISHED |
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: Raasay | Statement: [Dun Caan, locatedIn, Raasay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Raasay Context triple: [Dun Caan, locatedIn, Raasay]
-
A.
Raasay
chosen
Raasay is a small, sparsely populated Scottish island in the Inner Hebrides, known for its rugged landscapes, quiet villages, and views across to the Isle of Skye.
-
B.
Rasah
Rasah is a residential and administrative area within the city of Seremban in the Malaysian state of Negeri Sembilan.
-
C.
Raasiku
Raasiku is a small borough in northern Estonia that serves as the central settlement and administrative hub of Raasiku Parish.
-
D.
Raisuli
Raisuli is a charismatic Berber chieftain and anti-hero in the adventure film "The Wind and the Lion," loosely based on the historical Moroccan brigand Mulai Ahmed er Raisuni.
-
E.
Racha
Racha is a mountainous historical region in northwestern Georgia known for its scenic landscapes, traditional villages, and distinctive wines.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e3c4c5c81908d336165816b12e0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12a2e47a88190a3b5c05398605f68 |
completed | April 28, 2026, 9:44 p.m. |
Created at: April 16, 2026, 8:34 p.m.