Triple
T19746499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berat region |
E474264
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Berat |
—
|
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: Berat | Statement: [Berat region, hasCapital, Berat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Berat Context triple: [Berat region, hasCapital, Berat]
-
A.
Berat
chosen
Berat is a historic city in central Albania renowned for its well-preserved Ottoman architecture and hillside houses, earning it the nickname "the city of a thousand windows" and recognition as a UNESCO World Heritage Site.
-
B.
Buranda
Buranda is an inner-city suburb of Brisbane, Queensland, known for its major transport interchange and proximity to hospitals and shopping centres.
-
C.
Waase
Waase is a small village on the island of Ummanz in the German state of Mecklenburg-Vorpommern.
-
D.
Bara
Bara is a town in Pakistan’s Khyber District, known as a key settlement in the Khyber Pass region with strategic and commercial significance.
-
E.
Bara
Bara is a town in central Sudan known as an agricultural and trading center in North Kordofan State.
- 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65294b4008190818eda40630f4147 |
completed | April 20, 2026, 4:21 p.m. |
Created at: April 10, 2026, 1:47 p.m.