Triple

T35757712
Position Surface form Disambiguated ID Type / Status
Subject Saint Mary of Lleida E1033488 entity
Predicate hasTitleForm P2351 FINISHED
Object Santa Maria de Lleida
Santa Maria de Lleida is the Catalan name for Saint Mary of Lleida, a Marian dedication associated with the city of Lleida in Catalonia, Spain.
E2154599 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: Santa Maria de Lleida | Statement: [Saint Mary of Lleida, hasTitleForm, Santa Maria de Lleida]
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: Santa Maria de Lleida
Triple: [Saint Mary of Lleida, hasTitleForm, Santa Maria de Lleida]
Generated description
Santa Maria de Lleida is the Catalan name for Saint Mary of Lleida, a Marian dedication associated with the city of Lleida in Catalonia, Spain.

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_69f76e1262f48190a313318665acc189 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a1c138848190bdd27868794efd0f completed May 3, 2026, 7:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3885f897a08190badf29b5cc6dba37 completed June 22, 2026, 12:46 a.m.
NEDg Description generation batch_6a3887948e148190873b6efc5735127b completed June 22, 2026, 12:53 a.m.
NED2 Entity disambiguation (via description) batch_6a388849bf348190ba71468323566c56 completed June 22, 2026, 12:56 a.m.
Created at: May 3, 2026, 4:06 p.m.