Triple
T16416004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leppävaara |
E398685
|
entity |
| Predicate | hasShoppingCentre |
P4285
|
FINISHED |
| Object | Sello |
E290453
|
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: Sello | Statement: [Leppävaara, hasShoppingCentre, Sello]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sello Context triple: [Leppävaara, hasShoppingCentre, Sello]
-
A.
Sello
chosen
Sello is a major shopping and entertainment center located in Espoo, Finland, featuring a wide range of shops, restaurants, and cultural services.
-
B.
Selloi
The Selloi were the ancient priests associated with the oracle of Zeus at Dodona in Epirus, known from Homeric tradition.
-
C.
Stempel
Stempel is a surname most notably associated with Robert R. Stempel, the former chairman and CEO of General Motors.
-
D.
Saca
Saca is a Spanish-language surname most notably associated with former Salvadoran president Antonio Saca.
-
E.
Lingotto
Lingotto is a district in Turin, Italy, best known for its former Fiat automobile factory complex, now a major multi-purpose center with shopping, conference, and cultural facilities.
- 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_69d87f2b9024819085c20e52de95d583 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32877ff248190886717d3329421a7 |
completed | April 18, 2026, 6:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c6a89988190a44515f1ca08099f |
completed | May 10, 2026, 8:06 a.m. |
Created at: April 10, 2026, 5:09 a.m.