Triple

T2409067
Position Surface form Disambiguated ID Type / Status
Subject Transmeta E50342 entity
Predicate acquiredBy P347 FINISHED
Object Novafora
Novafora was a semiconductor company known for acquiring Transmeta to expand its presence in low-power microprocessor and video processing technologies.
 E262492 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: Novafora | Statement: [Transmeta, acquiredBy, Novafora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Novafora
Context triple: [Transmeta, acquiredBy, Novafora]
  • A. Versonnex
    Versonnex is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
  • B. Fremulon
    Fremulon is a television production company founded by Michael Schur, best known for producing acclaimed comedy series such as Brooklyn Nine-Nine.
  • C. Anpezan
    Anpezan is a regional dialect of the Ladin language spoken in parts of the Dolomite area of northern Italy.
  • D. Plegridy
    Plegridy is a pegylated interferon beta-1a medication used to treat relapsing forms of multiple sclerosis.
  • E. Vumerity
    Vumerity is an oral prescription medication used to treat relapsing forms of multiple sclerosis in adults.
  • 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: Novafora
Triple: [Transmeta, acquiredBy, Novafora]
Generated description
Novafora was a semiconductor company known for acquiring Transmeta to expand its presence in low-power microprocessor and video processing technologies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Novafora
Target entity description: Novafora was a semiconductor company known for acquiring Transmeta to expand its presence in low-power microprocessor and video processing technologies.
  • A. Versonnex
    Versonnex is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
  • B. Fremulon
    Fremulon is a television production company founded by Michael Schur, best known for producing acclaimed comedy series such as Brooklyn Nine-Nine.
  • C. Anpezan
    Anpezan is a regional dialect of the Ladin language spoken in parts of the Dolomite area of northern Italy.
  • D. Plegridy
    Plegridy is a pegylated interferon beta-1a medication used to treat relapsing forms of multiple sclerosis.
  • E. Vumerity
    Vumerity is an oral prescription medication used to treat relapsing forms of multiple sclerosis in adults.
  • 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_69a88b0339a88190a1207333cd271cc9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc925c6e481909bfd45b361d21963 completed March 7, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69aeb3edc63c8190ac6737bf28993f1b completed March 9, 2026, 11:50 a.m.
NEDg Description generation batch_69aeb4a5e9c481908426fe51343a1342 completed March 9, 2026, 11:53 a.m.
NED2 Entity disambiguation (via description) batch_69aeb52bec1881909c589aea2af3684c completed March 9, 2026, 11:55 a.m.
Created at: March 4, 2026, 7:58 p.m.