Triple
T20405090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kista |
E500446
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Västerort |
—
|
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: Västerort | Statement: [Kista, partOf, Västerort]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Västerort Context triple: [Kista, partOf, Västerort]
-
A.
Västerort
chosen
Västerort is the western suburban part of Stockholm, Sweden, consisting largely of residential districts and green areas outside the city center.
-
B.
Söderort
Söderort is the southern suburban part of Stockholm, Sweden, consisting mainly of residential districts located south of the inner-city island of Södermalm.
-
C.
Södertälje
Södertälje is a Swedish city southwest of Stockholm known for its industrial heritage, diverse population, and strategic location linking Lake Mälaren with the Baltic Sea via the Södertälje Canal.
-
D.
Fagersta
Fagersta is an industrial town in central Sweden known for its steel production and manufacturing heritage.
-
E.
Västerås
Västerås is a historic city in central Sweden known for its medieval cathedral, lakeside location on Lake Mälaren, and role as an important industrial and commercial center.
- 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_69e0b4a81bec8190b69adfdc1336a015 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6799161c48190825eca3027d1aa51 |
completed | April 20, 2026, 7:08 p.m. |
Created at: April 16, 2026, 11:29 a.m.