Triple
T3220429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Copenhagen Metro |
E67498
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Frederiksberg |
E255466
|
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: Frederiksberg | Statement: [Copenhagen Metro, serves, Frederiksberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frederiksberg Context triple: [Copenhagen Metro, serves, Frederiksberg]
-
A.
Frederiksberg
chosen
Frederiksberg is an affluent, centrally located municipality in Denmark that forms an enclave within the city of Copenhagen and is known for its parks, cultural institutions, and historic architecture.
-
B.
Ballerup
Ballerup is a suburban municipality near Copenhagen in eastern Denmark, known for its residential areas, business parks, and sports facilities.
-
C.
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.
-
D.
Rødovre
Rødovre is a suburban municipality in the Capital Region of Denmark, located just west of central Copenhagen.
-
E.
Kastrup
Kastrup is a district in the Tårnby Municipality near Copenhagen, Denmark, best known for hosting the country’s main international airport.
- 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_69ad858b8adc8190ad989712c87a476b |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adae16f20081909d7f3bac016f961d |
completed | March 8, 2026, 5:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2f3bb50b48190a1d2ea0dd71c039f |
completed | March 12, 2026, 5:11 p.m. |
Created at: March 8, 2026, 3:08 p.m.