Triple

T25144038
Position Surface form Disambiguated ID Type / Status
Subject Iglesia de San Eugenio de la Palma E629882 entity
Predicate hasParishStatus P13874 FINISHED
Object parish of Ciego de Ávila
The parish of Ciego de Ávila is a Roman Catholic ecclesiastical jurisdiction serving the faithful in and around the city of Ciego de Ávila, Cuba.
E1009003 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: parish of Ciego de Ávila | Statement: [Iglesia de San Eugenio de la Palma, hasParishStatus, parish of Ciego de Ávila]
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: parish of Ciego de Ávila
Triple: [Iglesia de San Eugenio de la Palma, hasParishStatus, parish of Ciego de Ávila]
Generated description
The parish of Ciego de Ávila is a Roman Catholic ecclesiastical jurisdiction serving the faithful in and around the city of Ciego de Ávila, Cuba.

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_69e2ff349e408190a6f4a5a66279f54d completed April 18, 2026, 3:49 a.m.
NER Named-entity recognition batch_69f4684b30a8819088fb9f78020c3e1a completed May 1, 2026, 8:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105d04dcb881909afaad0745d693f4 completed May 22, 2026, 1:41 p.m.
NEDg Description generation batch_6a105dd12cd08190b382c57952107fa6 completed May 22, 2026, 1:44 p.m.
NED2 Entity disambiguation (via description) batch_6a105edf54888190a3b77f63eb867749 completed May 22, 2026, 1:49 p.m.
Created at: April 18, 2026, 6:29 a.m.