Triple
T20405100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kista |
E500446
|
entity |
| Predicate | hasMetroStation |
P522
|
FINISHED |
| Object | Kista metro station |
—
|
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: Kista metro station | Statement: [Kista, hasMetroStation, Kista metro station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kista metro station Context triple: [Kista, hasMetroStation, Kista metro station]
-
A.
Kista metro station
chosen
Kista metro station is an underground station on Stockholm’s metro system serving the Kista district, a major hub for technology and business.
-
B.
Kristineberg metro station
Kristineberg metro station is a Stockholm Metro station on the green line, serving the Kristineberg district on Kungsholmen island in Sweden.
-
C.
Skanstull metro station
Skanstull metro station is a Stockholm Metro station on Södermalm that serves as a key stop on the city’s Green Line.
-
D.
Blackeberg metro station
Blackeberg metro station is a Stockholm Metro station on the Green line serving the Blackeberg district in western Stockholm, Sweden.
-
E.
Stockholm University metro station
Stockholm University metro station is a Stockholm Metro stop on the red line serving the university campus and surrounding areas in northeastern Stockholm.
- 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.