Triple
T5783040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skyscraper |
E128205
|
entity |
| Predicate | songwriter |
P1141
|
FINISHED |
| Object | Kerli Kõiv |
E543519
|
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: Kerli Kõiv | Statement: [Skyscraper, songwriter, Kerli Kõiv]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kerli Kõiv Context triple: [Skyscraper, songwriter, Kerli Kõiv]
-
A.
Kerli Kõiv
chosen
Kerli Kõiv is an Estonian singer-songwriter and producer known for her ethereal electropop style and visually distinctive, fairy-tale-inspired aesthetic.
-
B.
Sofi Oksanen
Sofi Oksanen is a Finnish-Estonian author and playwright renowned for her politically charged novels exploring Eastern European history, memory, and trauma, such as the internationally acclaimed "Purge."
-
C.
Jaan Kross
Jaan Kross was a prominent Estonian writer and poet, best known for his historical novels that explore Estonia’s past and its struggles under foreign rule.
-
D.
Melanija Knavs
Melanija Knavs is the Slovenian-born former fashion model who became First Lady of the United States as the wife of Donald Trump.
-
E.
Kersti Kaljulaid
Kersti Kaljulaid is an Estonian politician who served as the first female President of Estonia from 2016 to 2021.
- 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_69c0084450048190bc647b649a05136b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02a184870819084251554eae1e33c |
completed | March 22, 2026, 5:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c098112a1c8190a8aacb208c544959 |
completed | March 23, 2026, 1:32 a.m. |
Created at: March 22, 2026, 3:50 p.m.