Triple

T23789251
Position Surface form Disambiguated ID Type / Status
Subject Ventas E588044 entity
Predicate isNamedAfter P63 FINISHED
Object Las Ventas area
Las Ventas area is a neighborhood in Madrid best known for housing the iconic Plaza de Toros de Las Ventas, one of the world’s most famous bullrings.
 E1602463 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: Las Ventas area | Statement: [Ventas, isNamedAfter, Las Ventas area]
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: Las Ventas area
Triple: [Ventas, isNamedAfter, Las Ventas area]
Generated description
Las Ventas area is a neighborhood in Madrid best known for housing the iconic Plaza de Toros de Las Ventas, one of the world’s most famous bullrings.

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_69e2490f4ad48190b690878eec3596c6 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1c633f7908190bac7fdac5990920a completed April 29, 2026, 8:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f53ee67f48190a19da8ffa3edf95b completed May 21, 2026, 6:50 p.m.
NEDg Description generation batch_6a0f58f239ac8190ab0cc8cd7272a208 completed May 21, 2026, 7:11 p.m.
NED2 Entity disambiguation (via description) batch_6a0f59dfebe0819095c934359cb5dc24 completed May 21, 2026, 7:15 p.m.
Created at: April 17, 2026, 7:17 p.m.