Triple
T6158399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flemingsberg |
E137379
|
entity |
| Predicate | hasPostalArea |
P920
|
FINISHED |
| Object | Flemingsberg |
E137379
|
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: Flemingsberg | Statement: [Flemingsberg, hasPostalArea, Flemingsberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Flemingsberg Context triple: [Flemingsberg, hasPostalArea, Flemingsberg]
-
A.
Flemingsberg
chosen
Flemingsberg is a district in the southern Stockholm urban area known for its major university campus, hospital, and commuter rail hub.
-
B.
Gustavsberg
Gustavsberg is a locality in Sweden best known for its historic porcelain factory and role as a suburban community in the Stockholm archipelago.
-
C.
Skarpäng
Skarpäng is a residential urban area within Täby Municipality in Stockholm County, Sweden.
-
D.
Siljan
Siljan is a lake in Telemark, Norway, known for its scenic surroundings and proximity to the town of Skien.
-
E.
Eidskog
Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
- 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_69c008a54fc88190b6ce4416490ca79d |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05d32ef548190bc215d052d3497fe |
completed | March 22, 2026, 9:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1418ba6488190aaf8d3070555d60a |
completed | March 23, 2026, 1:35 p.m. |
Created at: March 22, 2026, 4:17 p.m.