Triple
T14425390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sgìre Nàiseanta Aillse |
E357681
|
entity |
| Predicate | hasNotableSettlement |
P14082
|
FINISHED |
| Object | Stoer |
E651798
|
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: Stoer | Statement: [Sgìre Nàiseanta Aillse, hasNotableSettlement, Stoer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stoer Context triple: [Sgìre Nàiseanta Aillse, hasNotableSettlement, Stoer]
-
A.
Stoer
chosen
Stoer is a small coastal village in the Assynt area of Sutherland in the Scottish Highlands, known for its rugged scenery and proximity to the Old Man of Stoer sea stack.
-
B.
Starnberg
Starnberg is a lakeside town in Bavaria, Germany, known for its affluent residential character and scenic location on Lake Starnberg southwest of Munich.
-
C.
Trendelburg
Trendelburg is a small historic town in northern Hesse, Germany, best known for its medieval castle and association with the Rapunzel fairy tale.
-
D.
Gersfeld
Gersfeld is a small German town in the state of Hesse, known as a gateway to the Rhön Mountains and a base for outdoor activities like hiking and winter sports.
-
E.
Weiler
Weiler is a village and district of the town of Schorndorf in the German state of Baden-Württemberg.
- 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91123f848190ba3fb18a76c2d24c |
completed | April 14, 2026, 7:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5bcd2a908190ad7d5ebf11b41551 |
completed | May 8, 2026, 3:43 a.m. |
Created at: April 10, 2026, 1:18 a.m.