Triple

T9949555
Position Surface form Disambiguated ID Type / Status
Subject Southern Great Plain region E195293 entity
Predicate containsCity P294 FINISHED
Object Orosháza
Orosháza is a town in southeastern Hungary known for its agricultural economy, thermal baths, and proximity to the Great Hungarian Plain.
E831510 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: Orosháza | Statement: [Southern Great Plain region, containsCity, Orosháza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orosháza
Context triple: [Southern Great Plain region, containsCity, Orosháza]
  • A. Orsa
    Orsa is a small locality and municipality in central Sweden known for its forests, lakes, and traditional Dalarna culture.
  • B. Yunaska
    Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
  • C. Hizaori
    Hizaori is the former name of Asaka, a city located in Saitama Prefecture, Japan.
  • D. Ogori
    Ogori is a small Japanese city located in Fukuoka Prefecture on the island of Kyushu.
  • E. Ozar
    Ozar is a town in the Nashik district of Maharashtra, India, known for its proximity to Nashik city and its role as a regional industrial and aviation hub.
  • 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: Orosháza
Triple: [Southern Great Plain region, containsCity, Orosháza]
Generated description
Orosháza is a town in southeastern Hungary known for its agricultural economy, thermal baths, and proximity to the Great Hungarian Plain.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Orosháza
Target entity description: Orosháza is a town in southeastern Hungary known for its agricultural economy, thermal baths, and proximity to the Great Hungarian Plain.
  • A. Orsa
    Orsa is a small locality and municipality in central Sweden known for its forests, lakes, and traditional Dalarna culture.
  • B. Yunaska
    Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
  • C. Hizaori
    Hizaori is the former name of Asaka, a city located in Saitama Prefecture, Japan.
  • D. Ogori
    Ogori is a small Japanese city located in Fukuoka Prefecture on the island of Kyushu.
  • E. Ozar
    Ozar is a town in the Nashik district of Maharashtra, India, known for its proximity to Nashik city and its role as a regional industrial and aviation hub.
  • 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_69ca82e96a108190932bd1fc4acd73a0 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb65a4e6c8190968192a24aad1b7d completed April 2, 2026, 12:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2292b50a881909ff868487639fbfd completed April 5, 2026, 9:19 a.m.
NEDg Description generation batch_69d22a2831348190909b9507edfe49f3 completed April 5, 2026, 9:23 a.m.
NED2 Entity disambiguation (via description) batch_69d22af8914c8190a8116a37a42b633c completed April 5, 2026, 9:27 a.m.
Created at: March 30, 2026, 8:45 p.m.