Triple
T17339138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telemark county (re-established) |
E421018
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Rjukan |
E422285
|
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: Rjukan | Statement: [Telemark county (re-established), contains, Rjukan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rjukan Context triple: [Telemark county (re-established), contains, Rjukan]
-
A.
Rjukan
chosen
Rjukan is a Norwegian industrial town in a deep valley in Telemark, known for its hydroelectric power heritage and World War II heavy water sabotage.
-
B.
Rygaard
Rygaard is a Danish surname most notably borne by professional footballer Markus Rygaard.
-
C.
Sillenbuch
Sillenbuch is a residential district in the southeast of Stuttgart, Germany, known for its green surroundings and suburban character.
-
D.
Stetinden
Stetinden is a distinctive, obelisk-shaped mountain in Nordland, Norway, renowned among climbers and often called Norway’s national mountain.
-
E.
Rissala
Rissala is a locality in Finland known primarily for hosting a major Finnish Air Force base associated with the Karelian Air Command.
- 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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a14ec90819098db2ac0d58a53e1 |
completed | April 19, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a018c56c8148190ab6e3e2eff09725e |
completed | May 11, 2026, 7:59 a.m. |
Created at: April 10, 2026, 5:44 a.m.