Triple

T223054
Position Surface form Disambiguated ID Type / Status
Subject Rijksmuseum E4257 entity
Predicate hasPart P35 FINISHED
Object Philips Wing
Philips Wing is a modern exhibition and gallery space within Amsterdam’s Rijksmuseum, often used for temporary and special exhibitions.
E28400 NE FINISHED

How this triple was built (4 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: Philips Wing | Statement: [Rijksmuseum, hasPart, Philips Wing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philips Wing
Context triple: [Rijksmuseum, hasPart, Philips Wing]
  • A. G-Wiz
    G-Wiz is the costumed, wizard-themed mascot who entertains fans at Washington Wizards basketball games.
  • B. Honeywell 316
    The Honeywell 316 is a 16-bit minicomputer introduced in the late 1960s, used widely for real-time control, industrial, and embedded applications.
  • C. Philortyx
    Philortyx is a genus of New World quails known for their ground-dwelling habits and occurrence in scrub and grassland habitats of the Americas.
  • D. Flivver
    Flivver is a colloquial nickname for the Ford Model T, the iconic early 20th-century mass-produced automobile that revolutionized personal transportation.
  • E. Dyson
    Dyson is a surname most famously associated with theoretical physicist and mathematician Freeman Dyson, known for his influential work in quantum electrodynamics and futurism.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Philips Wing
Triple: [Rijksmuseum, hasPart, Philips Wing]
Generated description
Philips Wing is a modern exhibition and gallery space within Amsterdam’s Rijksmuseum, often used for temporary and special exhibitions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Philips Wing
Target entity description: Philips Wing is a modern exhibition and gallery space within Amsterdam’s Rijksmuseum, often used for temporary and special exhibitions.
  • A. G-Wiz
    G-Wiz is the costumed, wizard-themed mascot who entertains fans at Washington Wizards basketball games.
  • B. Honeywell 316
    The Honeywell 316 is a 16-bit minicomputer introduced in the late 1960s, used widely for real-time control, industrial, and embedded applications.
  • C. Philortyx
    Philortyx is a genus of New World quails known for their ground-dwelling habits and occurrence in scrub and grassland habitats of the Americas.
  • D. Flivver
    Flivver is a colloquial nickname for the Ford Model T, the iconic early 20th-century mass-produced automobile that revolutionized personal transportation.
  • E. Dyson
    Dyson is a surname most famously associated with theoretical physicist and mathematician Freeman Dyson, known for his influential work in quantum electrodynamics and futurism.
  • F. None of above. chosen

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_69a2573508588190b522c2476d91acfe completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25c705fd88190bfee7f5e1f7cee17 completed Feb. 28, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69a34d96acd88190ae3c8c86bee2572c completed Feb. 28, 2026, 8:18 p.m.
NEDg Description generation batch_69a351694cf48190a87a4135868cab86 completed Feb. 28, 2026, 8:34 p.m.
NED2 Entity disambiguation (via description) batch_69a351c25af08190858e4d6644ddd75d completed Feb. 28, 2026, 8:36 p.m.
Created at: Feb. 28, 2026, 2:53 a.m.