Triple
T5334202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Veszprém County |
E123785
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Ajka |
E456759
|
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: Ajka | Statement: [Veszprém County, containsCity, Ajka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ajka Context triple: [Veszprém County, containsCity, Ajka]
-
A.
Ajka
chosen
Ajka is a town in western Hungary known for its industrial heritage, particularly in mining and alumina production.
-
B.
Paju
Paju is a city in South Korea near the Demilitarized Zone, known for its historical sites, cultural complexes, and role as a border hub with North Korea.
-
C.
Kirovakan
Kirovakan is the former name of Vanadzor, a major industrial city in northern Armenia.
-
D.
Nayki
Nayki is an island located within Lake Rakshastal in the Tibet Autonomous Region of China.
-
E.
Kars
Kars is a historic city in northeastern Turkey known for its medieval fortifications, strategic location near the Caucasus, and role as a former regional capital in various Armenian and Ottoman periods.
- 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_69bd464b07f8819095aa76577c9829e4 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85ae52c08190968a5567b7e6b794 |
completed | March 20, 2026, 5:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf18baeca081909acc11d0c6c89f6d |
completed | March 21, 2026, 10:16 p.m. |
Created at: March 20, 2026, 2 p.m.