Triple
T7005970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enebyberg |
E162456
|
entity |
| Predicate | nearbyLocality |
P4647
|
FINISHED |
| Object | Täby |
E20860
|
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: Täby | Statement: [Enebyberg, nearbyLocality, Täby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Täby Context triple: [Enebyberg, nearbyLocality, Täby]
-
A.
Täby Municipality
chosen
Täby Municipality is a suburban local government area north of central Stockholm, Sweden, known for its affluent residential neighborhoods and strong commuter links to the capital.
-
B.
Strängnäs
Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
-
C.
Tärnsjö
Tärnsjö is a small locality in central Sweden known for its rural setting and traditional leather tanning industry.
-
D.
Nykvarn
Nykvarn is a small locality in eastern Sweden that serves as the administrative and population center of Nykvarn Municipality in Stockholm County.
-
E.
Nässjö
Nässjö is a small Swedish town in Jönköping County known as a regional railway hub and service center in southern Sweden.
- 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_69c6885928148190ae31909fbb5e9849 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc34b5a88190a793e07dd4d0018b |
completed | March 27, 2026, 7:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c76a3f5a088190bd0fa2080a8fa648 |
completed | March 28, 2026, 5:42 a.m. |
Created at: March 27, 2026, 2:33 p.m.