Triple

T12190611
Position Surface form Disambiguated ID Type / Status
Subject Otaniemi E290450 entity
Predicate hasPart P35 FINISHED
Object Micronova
Micronova is a leading Finnish micro- and nanotechnology research and fabrication center located in Otaniemi, Espoo.
E964475 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: Micronova | Statement: [Otaniemi, hasPart, Micronova]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Micronova
Context triple: [Otaniemi, hasPart, Micronova]
  • A. Nicado
    Nicado is a Spanish-language surname most notably borne by Cuban mathematician and academic leader Miriam Nicado García.
  • B. Novaggio
    Novaggio is a small municipality in the canton of Ticino in southern Switzerland, known for its scenic hillside setting above Lake Lugano.
  • C. Metreon
    Metreon is a large entertainment and retail complex in downtown San Francisco featuring shops, restaurants, a movie theater, and event spaces.
  • D. Neometron
    Neometron is a company founded by computer scientist and software engineer Adele Goldberg, known for her pioneering work in object-oriented programming and graphical user interfaces.
  • E. Micronite
    Micronite is a brand of cigarette filter historically associated with Kent cigarettes, known for its controversial use of asbestos in early filter designs.
  • 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: Micronova
Triple: [Otaniemi, hasPart, Micronova]
Generated description
Micronova is a leading Finnish micro- and nanotechnology research and fabrication center located in Otaniemi, Espoo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Micronova
Target entity description: Micronova is a leading Finnish micro- and nanotechnology research and fabrication center located in Otaniemi, Espoo.
  • A. Nicado
    Nicado is a Spanish-language surname most notably borne by Cuban mathematician and academic leader Miriam Nicado García.
  • B. Novaggio
    Novaggio is a small municipality in the canton of Ticino in southern Switzerland, known for its scenic hillside setting above Lake Lugano.
  • C. Metreon
    Metreon is a large entertainment and retail complex in downtown San Francisco featuring shops, restaurants, a movie theater, and event spaces.
  • D. Neometron
    Neometron is a company founded by computer scientist and software engineer Adele Goldberg, known for her pioneering work in object-oriented programming and graphical user interfaces.
  • E. Micronite
    Micronite is a brand of cigarette filter historically associated with Kent cigarettes, known for its controversial use of asbestos in early filter designs.
  • 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_69d6ab64de5881908d56eb7a75c6cc69 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91c5340248190b79379423f3a3ca1 completed April 10, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f6b240f88190af916054869c3b95 completed May 2, 2026, 1:05 p.m.
NEDg Description generation batch_69f5ff826ea08190a6780351e4b927ac completed May 2, 2026, 1:43 p.m.
NED2 Entity disambiguation (via description) batch_69f60185ce8c8190abe3b1f633aac55d completed May 2, 2026, 1:52 p.m.
Created at: April 8, 2026, 9:50 p.m.