Triple

T24186110
Position Surface form Disambiguated ID Type / Status
Subject Fuente de Neptuno E599559 entity
Predicate locatedIn P40 FINISHED
Object Plaza de Cánovas del Castillo
Plaza de Cánovas del Castillo is a prominent square in central Madrid, Spain, known for its iconic Neptune Fountain and its location near major cultural and historic landmarks.
E1686933 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: Plaza de Cánovas del Castillo | Statement: [Fuente de Neptuno, locatedIn, Plaza de Cánovas del Castillo]
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: Plaza de Cánovas del Castillo
Triple: [Fuente de Neptuno, locatedIn, Plaza de Cánovas del Castillo]
Generated description
Plaza de Cánovas del Castillo is a prominent square in central Madrid, Spain, known for its iconic Neptune Fountain and its location near major cultural and historic landmarks.

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_69e288cdc8b88190bf2f835d3cb4ca28 completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1e2435f108190b1e48856b90234c4 completed April 29, 2026, 10:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10b6fa1aac8190b9579d78eb2ed69f completed May 22, 2026, 8:05 p.m.
NEDg Description generation batch_6a10b7fa6d60819097ff930865af4032 completed May 22, 2026, 8:09 p.m.
NED2 Entity disambiguation (via description) batch_6a10b9651af481909206495b2fc57a2e completed May 22, 2026, 8:15 p.m.
Created at: April 17, 2026, 11:35 p.m.