Triple

T30665026
Position Surface form Disambiguated ID Type / Status
Subject Santa Cruz quarter E780636 entity
Predicate hasPublicSpace P105 FINISHED
Object Plaza de los Venerables
Plaza de los Venerables is a small historic square in Seville’s Santa Cruz district, known for its charming architecture, outdoor cafés, and proximity to the Baroque Hospital de los Venerables.
E1962722 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 los Venerables | Statement: [Santa Cruz quarter, hasPublicSpace, Plaza de los Venerables]
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 los Venerables
Triple: [Santa Cruz quarter, hasPublicSpace, Plaza de los Venerables]
Generated description
Plaza de los Venerables is a small historic square in Seville’s Santa Cruz district, known for its charming architecture, outdoor cafés, and proximity to the Baroque Hospital de los Venerables.

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_69f224a6d10481909290be1a00fc83b3 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68ae3689c8190be2984edff634c52 completed May 2, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2b074dfda88190bfc8521eb15f3ef7 completed June 11, 2026, 7:06 p.m.
NEDg Description generation batch_6a2b08e7dafc81908eb21bcda0feb00e completed June 11, 2026, 7:13 p.m.
NED2 Entity disambiguation (via description) batch_6a2b095d5604819084b144741cc6b44b completed June 11, 2026, 7:15 p.m.
Created at: April 29, 2026, 8:31 p.m.