Triple

T34354723
Position Surface form Disambiguated ID Type / Status
Subject Olesa de Montserrat E881685 entity
Predicate locatedNear P294 FINISHED
Object Montserrat (mountain)
Montserrat is a distinctive multi-peaked mountain massif in Catalonia, Spain, famed for its serrated rock formations, Benedictine abbey, and religious and cultural significance.
E2094097 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: Montserrat (mountain) | Statement: [Olesa de Montserrat, locatedNear, Montserrat (mountain)]
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: Montserrat (mountain)
Triple: [Olesa de Montserrat, locatedNear, Montserrat (mountain)]
Generated description
Montserrat is a distinctive multi-peaked mountain massif in Catalonia, Spain, famed for its serrated rock formations, Benedictine abbey, and religious and cultural significance.

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_69f349bd06008190904c2f86c42749e3 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f713f76d1c8190807b59e2900ad399 completed May 3, 2026, 9:23 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37049cabfc8190817a649de7ddf46d completed June 20, 2026, 9:22 p.m.
NEDg Description generation batch_6a370655c9e88190843423032c10f74e completed June 20, 2026, 9:29 p.m.
NED2 Entity disambiguation (via description) batch_6a3706d092248190bc836c78f01deb84 completed June 20, 2026, 9:32 p.m.
Created at: May 1, 2026, 1:58 a.m.