Triple
T20628581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivo |
E506886
|
entity |
| Predicate | shortFormOf |
P43
|
FINISHED |
| Object | Ivomir |
—
|
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: Ivomir | Statement: [Ivo, shortFormOf, Ivomir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ivomir Context triple: [Ivo, shortFormOf, Ivomir]
-
A.
Radomir
Radomir is a town in western Bulgaria known for its location in the Pernik Province and its proximity to the Struma River and the capital, Sofia.
-
B.
Tihomir
chosen
Tihomir is a masculine given name of Slavic origin, commonly used in several countries of the Balkans.
-
C.
Chudomir
Chudomir was a renowned Bulgarian writer, humorist, and painter known for his satirical short stories and vivid depictions of rural life.
-
D.
Dragomir
Dragomir is a Swedish actor and former criminal best known internationally for his role in the film "Easy Money" and appearances in action movies and TV series.
-
E.
Milot
Milot is a historic town in northern Haiti best known as the site of the Sans-Souci Palace and near the Citadelle Laferrière, key monuments of Haiti’s post-independence era.
- 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_69e0b4bd4a0081908d4e97a590a33fb2 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abe771e88190a48471bf83b4804d |
completed | April 20, 2026, 10:42 p.m. |
Created at: April 16, 2026, 11:42 a.m.