Triple

T23913091
Position Surface form Disambiguated ID Type / Status
Subject Sé (Funchal parish) E601997 entity
Predicate contains P35 FINISHED
Object Funchal Cathedral
Funchal Cathedral is a late 15th–early 16th century Roman Catholic cathedral in Funchal, Madeira, renowned for its Manueline architecture and richly carved wooden ceiling.
E1609097 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: Funchal Cathedral | Statement: [Sé (Funchal parish), contains, Funchal Cathedral]
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: Funchal Cathedral
Triple: [Sé (Funchal parish), contains, Funchal Cathedral]
Generated description
Funchal Cathedral is a late 15th–early 16th century Roman Catholic cathedral in Funchal, Madeira, renowned for its Manueline architecture and richly carved wooden ceiling.

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_69e2953a187081908346a9f36e85fc98 completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f1ce96c47881908ccb17ef9f750676 completed April 29, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f763798e08190ad4ce45681f4fcf8 completed May 21, 2026, 9:16 p.m.
NEDg Description generation batch_6a0f77b76ab08190b2caf42777492249 completed May 21, 2026, 9:23 p.m.
NED2 Entity disambiguation (via description) batch_6a0f788c4c108190b79e1ea898be2a80 completed May 21, 2026, 9:26 p.m.
Created at: April 17, 2026, 8:39 p.m.