Triple

T24276450
Position Surface form Disambiguated ID Type / Status
Subject Hendrik Willem Mesdag E605422 entity
Predicate founded P104 FINISHED
Object Museum Mesdag
Museum Mesdag is an art museum in The Hague, Netherlands, renowned for its collection of 19th-century art and works by the Hague School assembled by painter Hendrik Willem Mesdag.
E1627732 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: Museum Mesdag | Statement: [Hendrik Willem Mesdag, founded, Museum Mesdag]
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: Museum Mesdag
Triple: [Hendrik Willem Mesdag, founded, Museum Mesdag]
Generated description
Museum Mesdag is an art museum in The Hague, Netherlands, renowned for its collection of 19th-century art and works by the Hague School assembled by painter Hendrik Willem Mesdag.

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_6a0fc9c2cb5c81909b8d4afd5bfbd163 completed May 22, 2026, 3:13 a.m.
NEDg Description generation batch_6a0fcb0d718c81909c02cea23a2bffdc completed May 22, 2026, 3:18 a.m.
NED2 Entity disambiguation (via description) batch_6a0fcbe6adc8819094c7d659d5ee63e3 completed May 22, 2026, 3:22 a.m.
Created at: April 18, 2026, 12:07 a.m.