Triple

T23977174
Position Surface form Disambiguated ID Type / Status
Subject Lokrum E604401 entity
Predicate hasLandmark P105 FINISHED
Object Maximilian’s summer residence
Maximilian’s summer residence is a historic 19th-century villa built by Archduke Maximilian of Habsburg on the island of Lokrum near Dubrovnik, Croatia.
E1613290 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: Maximilian’s summer residence | Statement: [Lokrum, hasLandmark, Maximilian’s summer residence]
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: Maximilian’s summer residence
Triple: [Lokrum, hasLandmark, Maximilian’s summer residence]
Generated description
Maximilian’s summer residence is a historic 19th-century villa built by Archduke Maximilian of Habsburg on the island of Lokrum near Dubrovnik, Croatia.

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_69e29543f40c819087700b7a272afb60 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1d2bad6ec81908b5649223a72c2b9 completed April 29, 2026, 9:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f7e7f8e94819089bcd8521a372b06 completed May 21, 2026, 9:51 p.m.
NEDg Description generation batch_6a0f7fa066c08190bd22cca33ae6cf3f completed May 21, 2026, 9:56 p.m.
NED2 Entity disambiguation (via description) batch_6a0f803e39408190b612e1bade70bac2 completed May 21, 2026, 9:59 p.m.
Created at: April 17, 2026, 9:26 p.m.