Triple
T20499639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rapla County |
E503265
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Aespa |
—
|
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: Aespa | Statement: [Rapla County, containsSettlement, Aespa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aespa Context triple: [Rapla County, containsSettlement, Aespa]
-
A.
Aespa
chosen
Aespa is a small village located in Kiili Parish in northern Estonia.
-
B.
Loona
Loona is a celebrated Punjabi epic verse play by Shiv Kumar Batalvi that reimagines the traditional legend of Puran Bhagat from the perspective of the vilified stepmother, Loona.
-
C.
Red Velvet
Red Velvet is a South Korean girl group under SM Entertainment known for their versatile music style that blends pop, R&B, and experimental sounds.
-
D.
Red Velvet
"Red Velvet" is a song by the American hip hop duo Outkast from their acclaimed 2000 album *Stankonia*, noted for its experimental production and socially conscious lyrics.
-
E.
Red Velvet
Red Velvet is the nickname of NBA shooting guard Kevin Huerter, known for his smooth shooting stroke and red hair.
- 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_69e0b4b1e52c8190894281cf7e3283ab |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69cc10cd08190915b6c29c6473f77 |
completed | April 20, 2026, 9:38 p.m. |
Created at: April 16, 2026, 11:35 a.m.