Triple
T3241601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amager Island |
E67975
|
entity |
| Predicate | hasProtectedArea |
P855
|
FINISHED |
| Object | Kalvebod Fælled |
E342323
|
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: Kalvebod Fælled | Statement: [Amager Island, hasProtectedArea, Kalvebod Fælled]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kalvebod Fælled Context triple: [Amager Island, hasProtectedArea, Kalvebod Fælled]
-
A.
Amager Fælled
chosen
Amager Fælled is a large urban nature reserve on Copenhagen’s Amager Island, known for its wetlands, meadows, and rich biodiversity amid the city.
-
B.
Østerdalen
Østerdalen is a large, sparsely populated valley region in Innlandet county, Norway, known for its forests, rivers, and traditional rural culture.
-
C.
Maarkedal
Maarkedal is a rural municipality in the Flemish Ardennes of East Flanders, Belgium, known for its hilly landscape and cycling routes.
-
D.
Rønne
Rønne is the largest town and administrative center of the Danish island of Bornholm, known for its historic harbor, half-timbered houses, and Baltic Sea ferry connections.
-
E.
Nyberg Woods
Nyberg Woods is a retail shopping center in Tualatin, Oregon, featuring a variety of stores, restaurants, and services.
- 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_69ad858d27348190abb61c280b4c86a9 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaef76d908190815bb456e366ee0a |
completed | March 8, 2026, 5:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e82f91788190a9b14613eab7a439 |
completed | March 12, 2026, 4:22 p.m. |
Created at: March 8, 2026, 3:08 p.m.