Triple
T20846356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ajka |
E513234
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Ajka District |
—
|
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: Ajka District | Statement: [Ajka, locatedIn, Ajka District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ajka District Context triple: [Ajka, locatedIn, Ajka District]
-
A.
Ajka District
chosen
Ajka District is an administrative district in western Hungary centered around the town of Ajka, within Veszprém County.
-
B.
Seoni district
Seoni district is an administrative district in the state of Madhya Pradesh, India, known for its forests, agriculture, and location in the Satpura hill region.
-
C.
Koléa District
Koléa District is an administrative district in northern Algeria, situated within Tipaza Province along the Mediterranean coast.
-
D.
Hangu District
Hangu District is an administrative district in Pakistan’s Khyber Pakhtunkhwa province, known for its strategic location and history of sectarian tensions.
-
E.
Jung District
Jung District is a central administrative and commercial district of Busan, South Korea, known for its historic markets, port-side location, and dense urban landscape.
- 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_69e0b4f4898081908209e58edb8f9c45 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c34ffb588190881953a0480b29a8 |
completed | April 21, 2026, 12:22 a.m. |
Created at: April 16, 2026, 12:43 p.m.