Triple

T15270947
Position Surface form Disambiguated ID Type / Status
Subject Carabobo E365018 entity
Predicate capital P234 FINISHED
Object Valencia
Valencia is one of Venezuela’s largest industrial and commercial cities, serving as a major economic and transportation hub in the country’s central region.
 E211349 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: Valencia | Statement: [Carabobo, capital, Valencia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Valencia
Context triple: [Carabobo, capital, Valencia]
  • A. 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.
  • B. Valencia
    Valencia was the original working title for the 2016 psychological thriller film "10 Cloverfield Lane."
  • C. Valencia
    Valencia is a major inland city in the Philippine province of Bukidnon, known as a commercial and agricultural hub in Northern Mindanao.
  • D. Valencia
    Valencia is a city located in the highland province of Bukidnon in the Philippines, known as a major agricultural and commercial center in the region.
  • E. Valencia
    Valencia is a genus of small, freshwater killifish native to Mediterranean Europe, known for inhabiting coastal streams and threatened aquatic habitats.
  • 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: Valencia
Triple: [Carabobo, capital, Valencia]
Generated description
Valencia is one of Venezuela’s largest industrial and commercial cities, serving as a major economic and transportation hub in the country’s central region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Valencia
Target entity description: Valencia is one of Venezuela’s largest industrial and commercial cities, serving as a major economic and transportation hub in the country’s central region.
  • A. Valencia chosen
    Valencia is a major industrial and commercial city in north-central Venezuela and the capital of Carabobo state.
  • B. 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.
  • C. Valencia
    Valencia is a major inland city in the Philippine province of Bukidnon, known as a commercial and agricultural hub in Northern Mindanao.
  • D. Valencia
    Valencia is a city in Ecuador that serves as the capital of Los Ríos Province’s Valencia Canton and is known for its agricultural surroundings and tropical climate.
  • E. Valencia
    Valencia is a city located in the highland province of Bukidnon in the Philippines, known as a major agricultural and commercial center in the region.
  • F. None of above.

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_69d85a0f08408190b3c3259ae35d79d2 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0094eac848190a1740ae1aa6b28e0 completed April 15, 2026, 9:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff677d34748190b5f723b5fd18b3a0 completed May 9, 2026, 4:57 p.m.
NEDg Description generation batch_69ff6856260c8190b82b40c484f87211 completed May 9, 2026, 5:01 p.m.
NED2 Entity disambiguation (via description) batch_69ff68e8e2c08190b460e23fe24f05e9 completed May 9, 2026, 5:03 p.m.
Created at: April 10, 2026, 3:14 a.m.