Triple
T2417528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hämeenlinna |
E52339
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Hillerød |
E95304
|
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: Hillerød | Statement: [Hämeenlinna, twinTown, Hillerød]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hillerød Context triple: [Hämeenlinna, twinTown, Hillerød]
-
A.
Hillerød
chosen
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.
-
B.
Rødovre
Rødovre is a suburban municipality in the Capital Region of Denmark, located just west of central Copenhagen.
-
C.
Holbæk
Holbæk is a coastal town and municipality in northwestern Zealand, Denmark, known for its harbor on Holbæk Fjord and role as a regional commercial and cultural center.
-
D.
Næstved
Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
-
E.
Ballerup
Ballerup is a suburban municipality near Copenhagen in eastern Denmark, known for its residential areas, business parks, and sports facilities.
- 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_69ab495622948190bc6bc6e4cddaf645 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc94eafd481909eeff689e5bf5960 |
completed | March 7, 2026, 6:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afaf32014c8190aa3cfea010c3bb39 |
completed | March 10, 2026, 5:42 a.m. |
Created at: March 6, 2026, 9:42 p.m.