Triple
T21091315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sätra |
E519643
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Söderort |
—
|
NE NERFINISHED |
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: Söderort | Statement: [Sätra, locatedIn, Söderort]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Söderort Context triple: [Sätra, locatedIn, Söderort]
-
A.
Söderort
chosen
Söderort is the southern suburban part of Stockholm, Sweden, consisting mainly of residential districts located south of the inner-city island of Södermalm.
-
B.
Söderhamn
Söderhamn is a coastal town in east-central Sweden known for its historical wooden architecture and role as the administrative and commercial center of the surrounding region.
-
C.
Västerort
Västerort is the western suburban part of Stockholm, Sweden, consisting largely of residential districts and green areas outside the city center.
-
D.
Sandviken
Sandviken is an industrial town in central Sweden, best known as the historic home of the steel company Sandvik.
-
E.
Oskarshamn
Oskarshamn is a coastal town in southeastern Sweden known for its Baltic Sea harbor and proximity to the island of Gotland.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b507dd9081908fb8bfcbef4c8b46 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7094ea7f881909db83bf6961b41ec |
completed | April 21, 2026, 5:21 a.m. |
Created at: April 16, 2026, 2:51 p.m.