Triple

T19574995
Position Surface form Disambiguated ID Type / Status
Subject Skien Municipality E489831 entity
Predicate contains P35 FINISHED
Object city of Skien E114133 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: city of Skien | Statement: [Skien Municipality, contains, city of Skien]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Skien
Context triple: [Skien Municipality, contains, city of Skien]
  • A. Skien chosen
    Skien is a historic city in southern Norway known as the birthplace of playwright Henrik Ibsen and as a regional commercial and industrial center.
  • B. Skien Municipality
    Skien Municipality is a local government area in Vestfold og Telemark county, Norway, encompassing the city of Skien and its surrounding communities.
  • C. Steinkjer
    Steinkjer is a town and municipality in central Norway that serves as an important regional center and administrative hub in Trøndelag county.
  • D. Sokna
    Sokna is an extinct Eastern Berber language formerly spoken around the oasis town of Sokna in central Libya.
  • E. Kristiansand
    Kristiansand is a coastal city in southern Norway known for its harbor, beaches, and role as a regional cultural and economic center.
  • 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_69d8e8dd9374819098e36349b3211663 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e64023fe148190900c6887896c8ea0 completed April 20, 2026, 3:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a07578feebc819097d233618e09d1eb completed May 15, 2026, 5:27 p.m.
Created at: April 10, 2026, 1:42 p.m.