Triple

T24276447
Position Surface form Disambiguated ID Type / Status
Subject Hendrik Willem Mesdag E605422 entity
Predicate educatedBy P335 FINISHED
Object Willem Roelofs
Willem Roelofs was a 19th-century Dutch landscape painter and leading figure of the Hague School, known for his atmospheric rural scenes and influence on younger artists.
 E1662288 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: Willem Roelofs | Statement: [Hendrik Willem Mesdag, educatedBy, Willem Roelofs]
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: Willem Roelofs
Triple: [Hendrik Willem Mesdag, educatedBy, Willem Roelofs]
Generated description
Willem Roelofs was a 19th-century Dutch landscape painter and leading figure of the Hague School, known for his atmospheric rural scenes and influence on younger artists.

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_69e2954707dc8190915551eb114cfff6 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f28d5fd03481908e502c6944d7fe69 completed April 29, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a104869bcf0819095141e29497e5741 completed May 22, 2026, 12:13 p.m.
NEDg Description generation batch_6a10496ad0748190b797fea89fc9472d completed May 22, 2026, 12:17 p.m.
NED2 Entity disambiguation (via description) batch_6a104bc667e48190bb0feadc5b324cde completed May 22, 2026, 12:27 p.m.
Created at: April 18, 2026, 12:07 a.m.