Triple
T12534395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helle Thorning-Schmidt |
E299650
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Rødovre |
E129268
|
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: Rødovre | Statement: [Helle Thorning-Schmidt, placeOfBirth, Rødovre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rødovre Context triple: [Helle Thorning-Schmidt, placeOfBirth, Rødovre]
-
A.
Rødovre
chosen
Rødovre is a suburban municipality in the Capital Region of Denmark, located just west of central Copenhagen.
-
B.
Birkerød
Birkerød is a suburban town in northeastern Zealand, Denmark, known for its residential character, green surroundings, and proximity to Copenhagen.
-
C.
Næstved
Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
-
D.
Nørresundby
Nørresundby is a town in northern Denmark situated across the Limfjord from Aalborg, forming part of the Aalborg metropolitan area.
-
E.
Hillerød
Hillerød is a Danish town on the island of Zealand, known for the historic Frederiksborg Castle and its role as a regional administrative and cultural center.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9546d3b2081908d3e0659f8f13678 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6685d8c64819088db715d7552d18d |
completed | May 2, 2026, 9:10 p.m. |
Created at: April 8, 2026, 9:57 p.m.