Triple

T5334210
Position Surface form Disambiguated ID Type / Status
Subject Veszprém County E123785 entity
Predicate containsTown P847 FINISHED
Object Berhida
Berhida is a small town in western Hungary known for its industrial background and location near the city of Veszprém.
 E512432 NE FINISHED

How this triple was built (4 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: Berhida | Statement: [Veszprém County, containsTown, Berhida]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Berhida
Context triple: [Veszprém County, containsTown, Berhida]
  • A. Bahraich
    Bahraich is a city in the Indian state of Uttar Pradesh, known for its location in the Terai region near the Nepal border and its historical and cultural significance.
  • B. Hillah
    Hillah is a city in central Iraq on the Euphrates River, known as the modern settlement adjacent to the ruins of ancient Babylon.
  • C. Bahau
    Bahau is a prominent town in the Malaysian state of Negeri Sembilan, serving as a local commercial and transportation hub for the surrounding rural areas.
  • D. Buin
    Buin is a Chilean town and commune located south of Santiago, known for its agricultural activity and the Buin Zoo.
  • E. Tarhuna
    Tarhuna is a town in northwestern Libya, southeast of Tripoli, known for its strategic role and tribal influence during the Libyan civil conflicts.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Berhida
Triple: [Veszprém County, containsTown, Berhida]
Generated description
Berhida is a small town in western Hungary known for its industrial background and location near the city of Veszprém.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Berhida
Target entity description: Berhida is a small town in western Hungary known for its industrial background and location near the city of Veszprém.
  • A. Bahraich
    Bahraich is a city in the Indian state of Uttar Pradesh, known for its location in the Terai region near the Nepal border and its historical and cultural significance.
  • B. Hillah
    Hillah is a city in central Iraq on the Euphrates River, known as the modern settlement adjacent to the ruins of ancient Babylon.
  • C. Bahau
    Bahau is a prominent town in the Malaysian state of Negeri Sembilan, serving as a local commercial and transportation hub for the surrounding rural areas.
  • D. Buin
    Buin is a Chilean town and commune located south of Santiago, known for its agricultural activity and the Buin Zoo.
  • E. Tarhuna
    Tarhuna is a town in northwestern Libya, southeast of Tripoli, known for its strategic role and tribal influence during the Libyan civil conflicts.
  • F. None of above. chosen

Provenance (5 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.
NEDg Description generation batch_69bf1a5440d8819094a6da0282408b7b completed March 21, 2026, 10:23 p.m.
NED2 Entity disambiguation (via description) batch_69bf1abe1ea88190b681eb18bfa361d7 completed March 21, 2026, 10:25 p.m.
Created at: March 20, 2026, 2 p.m.