Triple

T34517046
Position Surface form Disambiguated ID Type / Status
Subject Sant Ildefons E886179 entity
Predicate locatedOnStreet P959 FINISHED
Object Avinguda de Sant Ildefons
Avinguda de Sant Ildefons is a principal avenue in the Sant Ildefons area of Cornellà de Llobregat, near Barcelona, serving as a key local thoroughfare and reference point for the neighborhood.
E2216404 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: Avinguda de Sant Ildefons | Statement: [Sant Ildefons, locatedOnStreet, Avinguda de Sant Ildefons]
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: Avinguda de Sant Ildefons
Triple: [Sant Ildefons, locatedOnStreet, Avinguda de Sant Ildefons]
Generated description
Avinguda de Sant Ildefons is a principal avenue in the Sant Ildefons area of Cornellà de Llobregat, near Barcelona, serving as a key local thoroughfare and reference point for the neighborhood.

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_69f349ccc290819089d8e82698e53cb6 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f71f95ca408190b438f6444832dade completed May 3, 2026, 10:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a402b887e60819099b602124cd415db completed June 27, 2026, 7:59 p.m.
NEDg Description generation batch_6a402daca388819092fcfc9ca6316db3 completed June 27, 2026, 8:08 p.m.
NED2 Entity disambiguation (via description) batch_6a402fb5734c8190864a6094af82a89b completed June 27, 2026, 8:16 p.m.
Created at: May 1, 2026, 2:01 a.m.