Triple
T3531379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scottish Borders |
E74668
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Lauder |
E324591
|
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: Lauder | Statement: [Scottish Borders, containsSettlement, Lauder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lauder Context triple: [Scottish Borders, containsSettlement, Lauder]
-
A.
Lauder
chosen
Lauder is a small historic town in the Scottish Borders, known for its rural setting and nearby Thirlestane Castle.
-
B.
Henley
Henley is a small village and civil parish located in the county of Suffolk in eastern England.
-
C.
Avon
Avon is a suburban town in central Connecticut known for its residential communities, schools, and proximity to the Farmington Valley.
-
D.
Avon
Avon is a small town in Norfolk County, Massachusetts, known for its suburban character and proximity to the Greater Boston area.
-
E.
Saint-Laurent
Saint-Laurent is a borough of Montreal known as a major residential and industrial hub on the Island of Montreal in Quebec, Canada.
- 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_69ad85d1a3948190931fd1ea1f49717b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc988ee081909c6b9d5eed0d2d6d |
completed | March 8, 2026, 6:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b37e97536881908d5ed3dfe602c9e0 |
completed | March 13, 2026, 3:03 a.m. |
Created at: March 8, 2026, 3:19 p.m.