Triple
T7227726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Petrus |
E154823
|
entity |
| Predicate | hasVariantForm |
P457
|
FINISHED |
| Object | Petar |
E154824
|
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: Petar | Statement: [Petrus, hasVariantForm, Petar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Petar Context triple: [Petrus, hasVariantForm, Petar]
-
A.
Petar
chosen
Petar is a given name commonly used in Slavic countries, equivalent to the English name Peter.
-
B.
Predrag
Predrag is the given first name of former Serbian professional basketball player Peja Stojaković.
-
C.
Saša
Saša is a given name commonly used in Slavic countries, often as a diminutive of Aleksandar or Aleksandra.
-
D.
Vlatko
Vlatko is a masculine given name commonly used in Slavic countries, particularly in North Macedonia and other parts of the Balkans.
-
E.
Ilija
Ilija is a masculine given name of Slavic origin, commonly used in countries such as Bulgaria, Serbia, and North Macedonia.
- 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_69c68811dd1c8190ac460bb39e64e1f0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6e9df72cc81908d1c04e6e310fbb4 |
completed | March 27, 2026, 8:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7cc1cdfb88190934387e44531b732 |
completed | March 28, 2026, 12:39 p.m. |
Created at: March 27, 2026, 2:54 p.m.