Triple
T5334203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Veszprém County |
E123785
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Pápa |
E197323
|
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: Pápa | Statement: [Veszprém County, containsCity, Pápa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pápa Context triple: [Veszprém County, containsCity, Pápa]
-
A.
Pápa
chosen
Pápa is a Hungarian town that hosts a key NATO Strategic Airlift Capability air base, making it an important military and logistics hub in Central Europe.
-
B.
Vác
Vác is a historic town on the Danube in northern Hungary, known for its Baroque architecture and role as a regional cultural and religious center.
-
C.
Belá
Belá is a mountain river in northern Slovakia known for its clear waters, dynamic flow, and popularity among whitewater enthusiasts.
-
D.
Prazhskaya
Prazhskaya is a Moscow Metro station named after Prague, featuring Soviet-era architecture with Czech design influences.
-
E.
Esztergom
Esztergom is a historic Hungarian city on the Danube River that served as an early royal capital and remains a major religious and cultural center.
- 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.