Triple

T12469103
Position Surface form Disambiguated ID Type / Status
Subject Pyg Track E298005 entity
Predicate region P40 FINISHED
Object Snowdonia E47901 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: Snowdonia | Statement: [Pyg Track, region, Snowdonia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Snowdonia
Context triple: [Pyg Track, region, Snowdonia]
  • A. Snowdonia chosen
    Snowdonia is a mountainous region and national park in northwest Wales, renowned for its rugged landscapes, lakes, and the highest peak in Wales, Mount Snowdon.
  • B. Snowdon Massif
    Snowdon Massif is the central mountainous group in Snowdonia, Wales, encompassing Snowdon and its surrounding peaks and ridges.
  • C. Carnedd Llywelyn
    Carnedd Llywelyn is a prominent mountain in Snowdonia, Wales, known as one of the highest peaks in the country and a major summit of the Carneddau range.
  • D. 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.
  • E. Snowdon
    Snowdon is the tallest and most famous mountain in Wales, renowned for its scenic hiking routes and panoramic views.
  • 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_69d6ada270808190b1a2b2e7b02bb426 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94db979c481908778188794b2c08e completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64ba3983c8190aef5e3b6a6d2e41e completed May 2, 2026, 7:08 p.m.
Created at: April 8, 2026, 9:56 p.m.