Triple

T35801079
Position Surface form Disambiguated ID Type / Status
Subject Princess Karađorđević E1034978 entity
Predicate heldBy P8 FINISHED
Object Zorka Karađorđević
Zorka Karađorđević was a Serbian princess of the Karađorđević dynasty who became Princess of Montenegro through her marriage to Prince (later King) Nikola I Petrović-Njegoš.
E2188318 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: Zorka Karađorđević | Statement: [Princess Karađorđević, heldBy, Zorka Karađorđević]
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: Zorka Karađorđević
Triple: [Princess Karađorđević, heldBy, Zorka Karađorđević]
Generated description
Zorka Karađorđević was a Serbian princess of the Karađorđević dynasty who became Princess of Montenegro through her marriage to Prince (later King) Nikola I Petrović-Njegoš.

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_69f76e169bd081909f16cd8c9ee7870c completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a259cc048190806b33d9cdbe1a3b completed May 3, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39e6be66008190b08b91b49a0e3e48 completed June 23, 2026, 1:51 a.m.
NEDg Description generation batch_6a39e81406b481909017a0c2c458fa71 completed June 23, 2026, 1:57 a.m.
NED2 Entity disambiguation (via description) batch_6a39e8762fe88190b0b12577b3d30410 completed June 23, 2026, 1:59 a.m.
Created at: May 3, 2026, 4:06 p.m.