Triple
T1149723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ambleside |
E23647
|
entity |
| Predicate | hasNearbyVillage |
P4647
|
FINISHED |
| Object | Grasmere |
E22651
|
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: Grasmere | Statement: [Ambleside, hasNearbyVillage, Grasmere]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grasmere Context triple: [Ambleside, hasNearbyVillage, Grasmere]
-
A.
Grasmere
chosen
Grasmere is a picturesque village and lake in England’s Lake District, famed for its association with poet William Wordsworth and its scenic surroundings.
-
B.
Grasmere Lake
Grasmere Lake is a picturesque small lake in England’s Lake District, renowned for its scenic beauty and association with the poet William Wordsworth.
-
C.
Bowness-on-Windermere
Bowness-on-Windermere is a popular tourist town on the shores of Lake Windermere in England’s Lake District, known for its lakeside attractions and boating.
-
D.
Keswick
Keswick is a historic market town and popular tourist base in England’s Lake District, known for its scenic setting near Derwentwater and surrounding fells.
-
E.
Tideswell
Tideswell is a historic village in England’s Peak District, noted for its medieval church and traditional limestone architecture.
- 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_69a493f0d32c8190ac74bad3c87f2641 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bc730b008190bd0901e0a47a4b7a |
completed | March 1, 2026, 10:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac667a61248190b71033daadef58e3 |
completed | March 7, 2026, 5:55 p.m. |
Created at: March 1, 2026, 7:44 p.m.