Triple
T19143458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beg |
E468615
|
entity |
| Predicate | hasAlternativeForm |
P455
|
FINISHED |
| Object | Beğ |
—
|
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: Beğ | Statement: [Beg, hasAlternativeForm, Beğ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beğ Context triple: [Beg, hasAlternativeForm, Beğ]
-
A.
Beğ
chosen
Beğ is a historical Turkic title of nobility and leadership, roughly equivalent to "chieftain" or "lord," used across various Turkic and neighboring cultures.
-
B.
Beyeler
Beyeler is a Swiss surname most prominently associated with Ernst Beyeler, a renowned art dealer and founder of the Fondation Beyeler museum.
-
C.
Beylikova
Beylikova is a small town and district in central Turkey known for its agricultural activities and location within Eskişehir Province.
-
D.
Beşevler
Beşevler is a neighborhood in Bursa, Turkey, known for its educational institutions and urban residential character.
-
E.
Bahşili
Bahşili is a small town and district in central Turkey known for its rural character within Kırıkkale Province.
- 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_69d8dd0796a48190b34ce4cd9d3f3be5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e977fa208190aa8cafd0966599c6 |
completed | April 20, 2026, 8:53 a.m. |
Created at: April 10, 2026, 12:05 p.m.