Triple
T17022309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lejonbacken |
E412975
|
entity |
| Predicate | overlooks |
P1323
|
FINISHED |
| Object | Norrström |
E78000
|
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: Norrström | Statement: [Lejonbacken, overlooks, Norrström]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norrström Context triple: [Lejonbacken, overlooks, Norrström]
-
A.
Norrström
chosen
Norrström is a short but significant river in central Stockholm that connects Lake Mälaren with the Baltic Sea and flows past several of the city’s key historic and governmental buildings.
-
B.
Geijer
Geijer is a Swedish surname most notably associated with Erik Gustaf Geijer, a prominent 19th-century writer, historian, and philosopher.
-
C.
Norlén
Norlén is a Swedish surname most notably borne by politician Andreas Norlén, the Speaker of the Riksdag.
-
D.
Bäckström
Bäckström is a Swedish surname most prominently associated with NHL ice hockey star Nicklas Bäckström.
-
E.
Gyllensten
Gyllensten is a Swedish surname most notably associated with Lars Gyllensten, a prominent author and former member of the Swedish Academy.
- 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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d5d1d2e48190bbcba129247c6c2e |
completed | April 18, 2026, 7:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b4f9dfc819085639edb5cda1cca |
completed | May 10, 2026, 11:57 p.m. |
Created at: April 10, 2026, 5:33 a.m.