Triple

T17370212
Position Surface form Disambiguated ID Type / Status
Subject Upper Telemark E422289 entity
Predicate contains P35 FINISHED
Object Tinn NE ONNED1

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: Tinn | Statement: [Upper Telemark, contains, Tinn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tinn
Context triple: [Upper Telemark, contains, Tinn]
  • A. Tinn chosen
    Tinn is a mountainous municipality in Vestfold og Telemark county, Norway, known for the industrial town of Rjukan and its role in World War II heavy water sabotage.
  • B. Tineg
    Tineg is a remote, mountainous municipality in the province of Abra in the Philippines, known for its rugged terrain and largely rural, forested landscape.
  • C. Tysso
    Tysso is a river in the municipality of Ulvik in western Norway, known for flowing through a scenic fjord landscape.
  • D. Tinnum
    Tinnum is a village on the German North Sea island of Sylt, known for its historic Tinnum Castle earthwork and its proximity to the island’s main town, Westerland.
  • E. Tzia
    Tzia is an alternative name for Kea, a Greek island in the Cyclades known for its traditional villages, beaches, and proximity to Athens.
  • 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_69d889d6535c81908be333c01deaec4e completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a6842388190940235198fa50041 completed April 19, 2026, 2:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a019568a27c8190af1bbe6db75f3e6f in_progress May 11, 2026, 8:38 a.m.
Created at: April 10, 2026, 5:44 a.m.