Triple

T19996080
Position Surface form Disambiguated ID Type / Status
Subject Carabobo E494195 entity
Predicate hasMajorCity P316 FINISHED
Object Valencia
Valencia is the capital and largest city of Venezuela’s Carabobo state, known as an important industrial and economic center in the country.
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, hasMajorCity, Valencia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valencia
Context triple: [Carabobo, hasMajorCity, 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, hasMajorCity, Valencia]
Generated description
Valencia is the capital and largest city of Venezuela’s Carabobo state, known as an important industrial and economic center in the country.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Valencia
Target entity description: Valencia is the capital and largest city of Venezuela’s Carabobo state, known as an important industrial and economic center in the country.
  • 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 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.
  • 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 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 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_69da626b2d748190886981ea90c8b2ea completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e65fe3fb288190a935c334e8a5d54e completed April 20, 2026, 5:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a080e1e62dc81909c98de9676e80f97 completed May 16, 2026, 6:26 a.m.
NEDg Description generation batch_6a080f25c944819091dea5feb7ffb15a completed May 16, 2026, 6:31 a.m.
NED2 Entity disambiguation (via description) batch_6a080fbec30481909bc3c7a864785b61 completed May 16, 2026, 6:33 a.m.
Created at: April 11, 2026, 3:32 p.m.