Triple
T20395043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gransherad |
E500178
|
entity |
| Predicate | hasNeighboringArea |
P17964
|
FINISHED |
| Object | Tinn |
—
|
NE NERFINISHED |
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: [Gransherad, hasNeighboringArea, Tinn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tinn Context triple: [Gransherad, hasNeighboringArea, 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.
Tinka
Tinka is a literary work by German writer Volker Braun, known for its engagement with socialist themes and critical reflection on East German society.
-
C.
Tinka
Tinka is a fictional character portrayed by Danish actress Gerda Lie Kaas, likely in a Scandinavian film or television production.
-
D.
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.
-
E.
Tyin
Tyin is a mountain lake and surrounding highland area in Norway, known for its scenic landscapes, hiking opportunities, and role as a gateway to the Jotunheimen mountains.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4a71ebc8190b153a36c738730f4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67912d7948190ac2fda8ce95e5c70 |
completed | April 20, 2026, 7:05 p.m. |
Created at: April 16, 2026, 11:28 a.m.