Triple

T27048944
Position Surface form Disambiguated ID Type / Status
Subject Valera, Trujillo, Venezuela E684712 entity
Predicate locatedIn P40 FINISHED
Object Trujillo State
Trujillo State is a mountainous administrative region in western Venezuela known for its Andean landscapes, colonial towns, and agricultural production.
 E1766123 NE FINISHED

How this triple was built (2 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: Trujillo State | Statement: [Valera, Trujillo, Venezuela, locatedIn, Trujillo State]
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: Trujillo State
Triple: [Valera, Trujillo, Venezuela, locatedIn, Trujillo State]
Generated description
Trujillo State is a mountainous administrative region in western Venezuela known for its Andean landscapes, colonial towns, and agricultural production.

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_69ef14829fac8190914bef9ecc3005d7 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f622adb97c8190bdbea4bfa7ebe8c1 completed May 2, 2026, 4:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a129c8ae08c8190a6b93a6905443d84 completed May 24, 2026, 6:36 a.m.
NEDg Description generation batch_6a129d8d0cec8190866152cb9edfefe7 completed May 24, 2026, 6:41 a.m.
NED2 Entity disambiguation (via description) batch_6a129e0f2dc081909e404f6c9fcd3b0b completed May 24, 2026, 6:43 a.m.
Created at: April 27, 2026, 8:12 a.m.