Triple
T5338374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barkarby |
E123880
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Barkarby trading area |
E119530
|
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: Barkarby trading area | Statement: [Barkarby, contains, Barkarby trading area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barkarby trading area Context triple: [Barkarby, contains, Barkarby trading area]
-
A.
Barkarby retail area
chosen
Barkarby retail area is a major shopping and commercial district in Järfälla, Sweden, known for its large retail parks, outlet stores, and big-box retailers.
-
B.
Barkarby
Barkarby is a suburban district in the Stockholm urban area of Sweden, known for its residential neighborhoods, retail outlets, and the former Barkarby Airport site.
-
C.
Drusberg area
The Drusberg area is a mountainous region in the Swiss Alps known for its rugged terrain and alpine landscapes.
-
D.
Blackeberg
Blackeberg is a suburban district in western Stockholm, Sweden, best known internationally as the bleak, wintry backdrop of the Swedish vampire novel and film "Let the Right One In."
-
E.
Korangi Industrial Area
Korangi Industrial Area is a major industrial and manufacturing hub in Karachi, Pakistan, hosting numerous factories and businesses across diverse sectors.
- 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_69bd464b07f8819095aa76577c9829e4 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85c8415c819099a0b26e07360f01 |
completed | March 20, 2026, 5:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf18c54ca4819095ca1d81ee061937 |
completed | March 21, 2026, 10:16 p.m. |
Created at: March 20, 2026, 2 p.m.