Triple

T31343066
Position Surface form Disambiguated ID Type / Status
Subject Our Lady of Lledó E799360 entity
Predicate alsoKnownAs P39 FINISHED
Object Virgen de Lledó
Virgen de Lledó is a revered Marian devotion and patroness of Castellón de la Plana in Spain, centered on a historic image of the Virgin Mary venerated in the Basilica of Lledó.
E1961929 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: Virgen de Lledó | Statement: [Our Lady of Lledó, alsoKnownAs, Virgen de Lledó]
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: Virgen de Lledó
Triple: [Our Lady of Lledó, alsoKnownAs, Virgen de Lledó]
Generated description
Virgen de Lledó is a revered Marian devotion and patroness of Castellón de la Plana in Spain, centered on a historic image of the Virgin Mary venerated in the Basilica of Lledó.

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_69f224e51614819083141459a080e97c completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69f15d4f8819098892ed7905af38c completed May 3, 2026, 1:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b07621b388190bb5068fa7bb264e8 completed June 11, 2026, 7:07 p.m.
NEDg Description generation batch_6a2b081ac7788190a9ef51c13ff722e4 completed June 11, 2026, 7:10 p.m.
NED2 Entity disambiguation (via description) batch_6a2b08987f308190a93ba00410b5a0f3 completed June 11, 2026, 7:12 p.m.
Created at: April 29, 2026, 9:17 p.m.