Triple
T20405147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helenelund |
E500447
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Tureberg |
—
|
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: Tureberg | Statement: [Helenelund, adjacentTo, Tureberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tureberg Context triple: [Helenelund, adjacentTo, Tureberg]
-
A.
Tureberg
chosen
Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
-
B.
Radeberg
Radeberg is a small town in the German state of Saxony, known for its Radeberger Pilsner brewery and historic town center near Dresden.
-
C.
Trostberg
Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
-
D.
Radeburg
Radeburg is a small town in the German state of Saxony, situated north of Dresden and known for its historic center and surrounding rural landscape.
-
E.
Euerbach
Euerbach is a small municipality in the Schweinfurt district of northern Bavaria, Germany, known for its rural character and Franconian cultural heritage.
- 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_69e0b4a81bec8190b69adfdc1336a015 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6799161c48190825eca3027d1aa51 |
completed | April 20, 2026, 7:08 p.m. |
Created at: April 16, 2026, 11:29 a.m.