Triple

T1874065
Position Surface form Disambiguated ID Type / Status
Subject Valencian Community E39098 entity
Predicate hasMajorCity P316 FINISHED
Object Torrevieja
Torrevieja is a coastal city in southeastern Spain known for its salt lakes, beaches, and tourism-driven economy.
E221170 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: Torrevieja | Statement: [Valencian Community, hasMajorCity, Torrevieja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Torrevieja
Context triple: [Valencian Community, hasMajorCity, Torrevieja]
  • A. Estepona
    Estepona is a coastal resort town on Spain’s Costa del Sol, known for its Mediterranean beaches, marina, and whitewashed old town.
  • B. Almería
    Almería is a coastal city and province in southeastern Spain known for its arid climate, historic Alcazaba fortress, and extensive greenhouse agriculture.
  • C. Málaga
    Málaga is a historic port city on Spain’s Costa del Sol, renowned for its Mediterranean beaches, rich Andalusian culture, and as the birthplace of artist Pablo Picasso.
  • D. Valencia
    Valencia is a major Spanish coastal city known for its historic architecture, vibrant culture, and significant role as a key Mediterranean trade and tourism hub.
  • E. Valencia
    Valencia is a major industrial and commercial city in north-central Venezuela and the capital of Carabobo state.
  • 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: Torrevieja
Triple: [Valencian Community, hasMajorCity, Torrevieja]
Generated description
Torrevieja is a coastal city in southeastern Spain known for its salt lakes, beaches, and tourism-driven economy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Torrevieja
Target entity description: Torrevieja is a coastal city in southeastern Spain known for its salt lakes, beaches, and tourism-driven economy.
  • A. Estepona
    Estepona is a coastal resort town on Spain’s Costa del Sol, known for its Mediterranean beaches, marina, and whitewashed old town.
  • B. Almería
    Almería is a coastal city and province in southeastern Spain known for its arid climate, historic Alcazaba fortress, and extensive greenhouse agriculture.
  • C. Málaga
    Málaga is a historic port city on Spain’s Costa del Sol, renowned for its Mediterranean beaches, rich Andalusian culture, and as the birthplace of artist Pablo Picasso.
  • D. Valencia
    Valencia is a major Spanish coastal city known for its historic architecture, vibrant culture, and significant role as a key Mediterranean trade and tourism hub.
  • E. Valencia
    Valencia is a major industrial and commercial city in north-central Venezuela and the capital of Carabobo state.
  • 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_69a8862f7074819096afe7fe65e179e9 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb0d648ec8190a21445ddca6f9aa6 completed March 7, 2026, 5 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae030bfbcc8190842a2bc69afb0db2 completed March 8, 2026, 11:15 p.m.
NEDg Description generation batch_69ae03647d5881908c5952dd3e2015a7 completed March 8, 2026, 11:16 p.m.
NED2 Entity disambiguation (via description) batch_69ae03f3611c8190b1cb90c9e59429cc completed March 8, 2026, 11:19 p.m.
Created at: March 4, 2026, 7:34 p.m.