Triple
T13575608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Llanberis |
E324273
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Snowdon |
E61320
|
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: Snowdon | Statement: [Llanberis, near, Snowdon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Snowdon Context triple: [Llanberis, near, Snowdon]
-
A.
Snowdon
Snowdon is a major Montreal Metro station in the Côte-des-Neiges–Notre-Dame-de-Grâce borough that serves as an important transfer point between multiple subway lines.
-
B.
Snowdon
chosen
Snowdon is the tallest and most famous mountain in Wales, renowned for its scenic hiking routes and panoramic views.
-
C.
Tryfan
Tryfan is a distinctive, rugged mountain in Snowdonia, Wales, famed for its jagged profile and popular scrambling routes.
-
D.
Eryri
Eryri is the Welsh name for Snowdonia, a mountainous national park in northwest Wales known for its rugged peaks, lakes, and scenic landscapes.
-
E.
Snowdon Massif
Snowdon Massif is the central mountainous group in Snowdonia, Wales, encompassing Snowdon and its surrounding peaks and ridges.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb02b1f108190a12af382d1de70bb |
completed | April 12, 2026, 2:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78ae008788190b3ebc09e73ec4952 |
completed | May 3, 2026, 5:50 p.m. |
Created at: April 9, 2026, 9:48 p.m.