Triple

T36080200
Position Surface form Disambiguated ID Type / Status
Subject historic center of Koper E1043623 entity
Predicate hasLandmark P105 FINISHED
Object Church of St Nicholas (Koper)
The Church of St Nicholas in Koper is a historic Roman Catholic church and notable architectural landmark situated in the old town of this coastal Slovenian city.
E2174253 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: Church of St Nicholas (Koper) | Statement: [historic center of Koper, hasLandmark, Church of St Nicholas (Koper)]
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: Church of St Nicholas (Koper)
Triple: [historic center of Koper, hasLandmark, Church of St Nicholas (Koper)]
Generated description
The Church of St Nicholas in Koper is a historic Roman Catholic church and notable architectural landmark situated in the old town of this coastal Slovenian city.

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_69f76e3154908190a6f702671c2bea08 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b23c3e308190915e51b2f1068fba completed May 3, 2026, 8:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3933fe40c48190b97a6a688a4eed73 completed June 22, 2026, 1:09 p.m.
NEDg Description generation batch_6a39357be9248190ac0dc9a49cf9bc05 completed June 22, 2026, 1:15 p.m.
NED2 Entity disambiguation (via description) batch_6a393617dfbc8190a9098be4065253b7 completed June 22, 2026, 1:18 p.m.
Created at: May 3, 2026, 4:08 p.m.