Triple
T15021793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stetinden |
E378101
|
entity |
| Predicate | languageName |
P13426
|
FINISHED |
| Object | Stetinden |
E378101
|
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: Stetinden | Statement: [Stetinden, languageName, Stetinden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stetinden Context triple: [Stetinden, languageName, Stetinden]
-
A.
Stetinden
chosen
Stetinden is a distinctive, obelisk-shaped mountain in Nordland, Norway, renowned among climbers and often called Norway’s national mountain.
-
B.
Standen
Standen is an Arts and Crafts country house in West Sussex, England, designed in the late 19th century by architect Philip Webb for the Beale family and now cared for by the National Trust.
-
C.
Stavenisse
Stavenisse is a small village in the Dutch province of Zeeland, located on the island of Tholen and known for its dike landscapes and fishing heritage.
-
D.
Stößen
Stößen is a small town in the German state of Saxony-Anhalt that forms part of the broader Leipzig metropolitan area.
-
E.
Rjukan
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.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded765462c819097f331c9b39c80e3 |
completed | April 15, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9dd2c96c8190a0368678584aaa16 |
completed | May 9, 2026, 2:37 a.m. |
Created at: April 10, 2026, 2:56 a.m.