Triple
T16255948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rolava |
E394626
|
entity |
| Predicate | hasBridgeIn |
P50312
|
FINISHED |
| Object | Nejdek |
E1202534
|
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: Nejdek | Statement: [Rolava, hasBridgeIn, Nejdek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nejdek Context triple: [Rolava, hasBridgeIn, Nejdek]
-
A.
Nejdek
chosen
Nejdek is a small town in the Karlovy Vary Region of the Czech Republic, known for its historical mining heritage and location in the Ore Mountains.
-
B.
Nekede
Nekede is a suburban community in Imo State, Nigeria, known for hosting the Federal Polytechnic Nekede and lying on the outskirts of the city of Owerri.
-
C.
Neka
Neka is a city in northern Iran known for its location near the Caspian Sea and its role as an industrial and agricultural center in Mazandaran Province.
-
D.
Neydens
Neydens is a small commune in southeastern France’s Haute-Savoie department, near the Swiss border and the city of Geneva.
-
E.
Nejd
Nejd is a vast central region of the Arabian Peninsula that historically served as the heartland of the Saudi state and the birthplace of its ruling dynasty.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2459a48f081909c76b38741b8f04e |
completed | April 17, 2026, 2:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0017b1e22c8190bddca67661121c2d |
completed | May 10, 2026, 5:29 a.m. |
Created at: April 10, 2026, 5:04 a.m.