Triple

T8109250
Position Surface form Disambiguated ID Type / Status
Subject Prahova County E189305 entity
Predicate hasTown P847 FINISHED
Object Câmpina
Câmpina is a town in southern Romania known historically as an important oil industry center and a gateway to the Prahova Valley.
 E712681 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: Câmpina | Statement: [Prahova County, hasTown, Câmpina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Câmpina
Context triple: [Prahova County, hasTown, Câmpina]
  • A. Ciampea
    Ciampea is a district in West Java, Indonesia, known as part of the suburban and semi-rural area surrounding the city of Bogor.
  • B. Piana
    Piana is a picturesque coastal village in western Corsica, France, renowned for its dramatic red granite cliffs and proximity to the UNESCO-listed Gulf of Porto and Calanche de Piana.
  • C. Altaelva
    Altaelva is a major river in northern Norway known for flowing through the Alta region and its surrounding Arctic landscapes.
  • D. Vegueta
    Vegueta is the historic old quarter of Las Palmas de Gran Canaria, known for its colonial architecture, cobbled streets, and cultural landmarks.
  • E. Raposeira
    Raposeira is a small village in Portugal’s Algarve region, known for its rural charm and proximity to the Atlantic coast near Vila do Bispo.
  • 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: Câmpina
Triple: [Prahova County, hasTown, Câmpina]
Generated description
Câmpina is a town in southern Romania known historically as an important oil industry center and a gateway to the Prahova Valley.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Câmpina
Target entity description: Câmpina is a town in southern Romania known historically as an important oil industry center and a gateway to the Prahova Valley.
  • A. Ciampea
    Ciampea is a district in West Java, Indonesia, known as part of the suburban and semi-rural area surrounding the city of Bogor.
  • B. Piana
    Piana is a picturesque coastal village in western Corsica, France, renowned for its dramatic red granite cliffs and proximity to the UNESCO-listed Gulf of Porto and Calanche de Piana.
  • C. Altaelva
    Altaelva is a major river in northern Norway known for flowing through the Alta region and its surrounding Arctic landscapes.
  • D. Vegueta
    Vegueta is the historic old quarter of Las Palmas de Gran Canaria, known for its colonial architecture, cobbled streets, and cultural landmarks.
  • E. Raposeira
    Raposeira is a small village in Portugal’s Algarve region, known for its rural charm and proximity to the Atlantic coast near Vila do Bispo.
  • 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_69ca82b9d5848190a24672775d5c5011 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb42fbc57c81908c6be87bbc547085 completed March 31, 2026, 3:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc9421794081909170ea11b09ae357 completed April 1, 2026, 3:42 a.m.
NEDg Description generation batch_69cc95bfb2b08190ae4bbf8fdde3165d completed April 1, 2026, 3:49 a.m.
NED2 Entity disambiguation (via description) batch_69cc97781c0481909d21293633d111be completed April 1, 2026, 3:56 a.m.
Created at: March 30, 2026, 5:32 p.m.