Triple
T12259635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Celia |
E292186
|
entity |
| Predicate | hasSingle |
P3282
|
FINISHED |
| Object | Koroba |
E977100
|
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: Koroba | Statement: [Celia, hasSingle, Koroba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Koroba Context triple: [Celia, hasSingle, Koroba]
-
A.
Koroba
chosen
"Koroba" is a popular Afrobeats song by Nigerian singer Tiwa Savage, known for its catchy rhythm and socially conscious lyrics.
-
B.
Ozerki
Ozerki is a locality in Russia historically noted as the site where the revolutionary priest Georgy Gapon was killed.
-
C.
Yastrebets
Yastrebets is a prominent peak in Bulgaria’s Rila Mountains, known for its ski slopes and panoramic views within the Borovets resort area.
-
D.
Korukivka
Korukivka is a small city in northern Ukraine known for its location within the Chernihiv region and its historical significance, including tragic events during World War II.
-
E.
Oreshek
Oreshek is the historic Russian fortress on Lake Ladoga that later gave rise to the town of Shlisselburg.
- 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_69d6ab6856488190b5d31178d5015f8e |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cd964ec81908241d2b9a96d1025 |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63eea69448190b5c57a74f4d20dca |
completed | May 2, 2026, 6:14 p.m. |
Created at: April 8, 2026, 9:52 p.m.