Triple
T10885678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johan Söderqvist |
E257038
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Söderqvist |
E257038
|
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: Söderqvist | Statement: [Johan Söderqvist, familyName, Söderqvist]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Söderqvist Context triple: [Johan Söderqvist, familyName, Söderqvist]
-
A.
Söderblom
Söderblom is a Swedish surname most notably associated with Nathan Söderblom, the Nobel Peace Prize–winning Lutheran archbishop and ecumenical leader.
-
B.
Bäckström
Bäckström is a Swedish surname most prominently associated with NHL ice hockey star Nicklas Bäckström.
-
C.
Söderfors
Söderfors is a small locality in Uppsala County, Sweden, known historically for its ironworks and scenic location by the Dalälven river.
-
D.
Gyllensten
Gyllensten is a Swedish surname most notably associated with Lars Gyllensten, a prominent author and former member of the Swedish Academy.
-
E.
Johan Söderqvist
chosen
Johan Söderqvist is a Swedish film composer known for his atmospheric and emotionally nuanced scores for Scandinavian and international cinema.
- 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_69d6aa848804819081b2713ca0bedf06 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d751dd6a3c81909965ef774e8b7309 |
completed | April 9, 2026, 7:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dff7ecf1c48190aef0d31ef03d1f88 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 8, 2026, 9:21 p.m.