Triple

T17732022
Position Surface form Disambiguated ID Type / Status
Subject Namdalen E442609 entity
Predicate hasPart P35 FINISHED
Object Lierne E592933 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: Lierne | Statement: [Namdalen, hasPart, Lierne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lierne
Context triple: [Namdalen, hasPart, Lierne]
  • A. Lierne chosen
    Lierne is a sparsely populated municipality in Trøndelag county, Norway, known for its vast wilderness areas, national parks, and rich wildlife.
  • B. Lierna
    Lierna is a small lakeside village on the eastern shore of Lake Como in northern Italy, known for its scenic views and historic stone hamlets.
  • C. Selybria
    Selybria is an ancient city of historical significance located in the region of Thrace, near the coast of the Sea of Marmara.
  • D. Laer
    Laer is a small municipality in the Steinfurt district of North Rhine-Westphalia, Germany, known for its rural character and traditional Westphalian architecture.
  • E. Leunovo
    Leunovo is a small village located in the mountainous Mavrovo region of North Macedonia, known for its natural scenery and proximity to Mavrovo National Park.
  • 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_69d8b9ec79688190b86bdcef85a7b3aa completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e478e7773081909dadb90ff5cb0906 completed April 19, 2026, 6:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a02efaf24d48190a535eba40ae33443 completed May 12, 2026, 9:15 a.m.
Created at: April 10, 2026, 10:08 a.m.