Triple
T8629763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saša |
E204369
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Aleksa |
E204369
|
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: Aleksa | Statement: [Saša, relatedName, Aleksa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aleksa Context triple: [Saša, relatedName, Aleksa]
-
A.
Saša
chosen
Saša is a given name commonly used in Slavic countries, often as a diminutive of Aleksandar or Aleksandra.
-
B.
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.
-
C.
Ilija
Ilija is a masculine given name of Slavic origin, commonly used in countries such as Bulgaria, Serbia, and North Macedonia.
-
D.
Aleksandar
Aleksandar is a masculine given name commonly used in Slavic countries, equivalent to Alexander.
-
E.
Petar
Petar is a given name commonly used in Slavic countries, equivalent to the English name Peter.
- 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_69ca834a4ea0819094970dceb9e389f3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc47406efc8190b559c68764b7455d |
completed | March 31, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cef354c5c08190bf7d3023a3473d2f |
completed | April 2, 2026, 10:53 p.m. |
Created at: March 30, 2026, 6:27 p.m.