Triple
T20259840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Torņakalns campus |
E498802
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Torņakalns, Riga, Latvia |
—
|
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: Torņakalns, Riga, Latvia | Statement: [Torņakalns campus, locatedIn, Torņakalns, Riga, Latvia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Torņakalns, Riga, Latvia Context triple: [Torņakalns campus, locatedIn, Torņakalns, Riga, Latvia]
-
A.
Liepāja, Latvia
Liepāja is a major port city on Latvia’s Baltic Sea coast, known for its historic architecture, naval heritage, and cultural life.
-
B.
Aizkraukle, Latvia
Aizkraukle is a small town in central Latvia on the right bank of the Daugava River, known as a regional administrative center and former Soviet-era hydroelectric power plant settlement.
-
C.
Riga
Riga is a town in the Sitamarhi district of the Indian state of Bihar.
-
D.
Riga
chosen
Riga is the capital and largest city of Latvia, a historic cultural and economic hub on the Baltic Sea known for its Art Nouveau architecture and significant port.
-
E.
Riga Central District
Riga Central District is a central administrative area of Riga, Latvia, encompassing key urban streets, commercial zones, and cultural landmarks.
- 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e674c90d00819082f68822635ee86a |
completed | April 20, 2026, 6:47 p.m. |
Created at: April 11, 2026, 11:41 p.m.