Triple
T4581771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jutland |
E101870
|
entity |
| Predicate | highestPoint |
P210
|
FINISHED |
| Object | Ejer Bavnehøj |
E176944
|
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: Ejer Bavnehøj | Statement: [Jutland, highestPoint, Ejer Bavnehøj]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ejer Bavnehøj Context triple: [Jutland, highestPoint, Ejer Bavnehøj]
-
A.
Ejer Bavnehøj
chosen
Ejer Bavnehøj is a prominent hill in eastern Jutland, Denmark, known as one of the country's highest natural points and a popular viewpoint.
-
B.
Hornbæk
Hornbæk is a coastal town in northern Zealand, Denmark, known for its sandy beaches, holiday villas, and role as a popular seaside resort.
-
C.
Norderhov
Norderhov is a village in the municipality of Ringerike in Buskerud, Norway, known for its historic church and rural surroundings.
-
D.
Henkersteg
Henkersteg is a historic wooden footbridge in Nuremberg, Germany, known for its medieval architecture and picturesque crossing over the Pegnitz River.
-
E.
Hellebæk
Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
- 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_69bd43d4ce208190b53158c882b222e3 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd590116e88190b8495b2a78cf3fb6 |
completed | March 20, 2026, 2:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bde09015c48190b4f992f3f95023cf |
completed | March 21, 2026, 12:04 a.m. |
Created at: March 20, 2026, 1:10 p.m.