Triple

T36908283
Position Surface form Disambiguated ID Type / Status
Subject Ban of Croatia E912835 entity
Predicate positionHeldBy P8 FINISHED
Object Juraj Haulik
Juraj Haulik was a 19th-century Croatian prelate and statesman who served as Ban of Croatia and played a key role in the country’s political and cultural life within the Habsburg Monarchy.
E2285514 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: Juraj Haulik | Statement: [Ban of Croatia, positionHeldBy, Juraj Haulik]
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: Juraj Haulik
Triple: [Ban of Croatia, positionHeldBy, Juraj Haulik]
Generated description
Juraj Haulik was a 19th-century Croatian prelate and statesman who served as Ban of Croatia and played a key role in the country’s political and cultural life within the Habsburg Monarchy.

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_69f76e879768819085c2fb31a6a5b44b completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f9fdac94a0819090d0dd980eb38377 completed May 5, 2026, 2:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a45f1e5484c819080b4fa4809cc17b2 completed July 2, 2026, 5:06 a.m.
NEDg Description generation batch_6a45f62ded008190a5ac436d6af1a661 completed July 2, 2026, 5:25 a.m.
NED2 Entity disambiguation (via description) batch_6a45f73fb2d48190b50aac074636e7a4 completed July 2, 2026, 5:29 a.m.
Created at: May 3, 2026, 4:13 p.m.