Triple

T28801943
Position Surface form Disambiguated ID Type / Status
Subject Bușteni E727259 entity
Predicate hasTouristAttraction P530 FINISHED
Object Cantacuzino Castle
Cantacuzino Castle is a historic Neo-Romanian style palace in the Carpathian Mountains of Romania, known for its scenic setting, architectural elegance, and role as a cultural and tourist landmark.
E1833013 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: Cantacuzino Castle | Statement: [Bușteni, hasTouristAttraction, Cantacuzino Castle]
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: Cantacuzino Castle
Triple: [Bușteni, hasTouristAttraction, Cantacuzino Castle]
Generated description
Cantacuzino Castle is a historic Neo-Romanian style palace in the Carpathian Mountains of Romania, known for its scenic setting, architectural elegance, and role as a cultural and tourist landmark.

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_69f0319b7c44819085736bcc256185e6 completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f658ab67888190af811176679f6714 completed May 2, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24a27bc5748190ab76be2f66d8faa7 completed June 6, 2026, 10:43 p.m.
NEDg Description generation batch_6a24a703ae6c8190b6298c1283e7c9b7 completed June 6, 2026, 11:02 p.m.
NED2 Entity disambiguation (via description) batch_6a24ab4ed6088190a8de9ed2255599ea completed June 6, 2026, 11:20 p.m.
Created at: April 28, 2026, 6:27 a.m.