Triple

T1447225
Position Surface form Disambiguated ID Type / Status
Subject Jeff Bezos E31204 entity
Predicate employer P7 FINISHED
Object Fitel
Fitel was a financial technology startup where Jeff Bezos worked early in his career, before joining D. E. Shaw and later founding Amazon.
 E165766 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: Fitel | Statement: [Jeff Bezos, employer, Fitel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fitel
Context triple: [Jeff Bezos, employer, Fitel]
  • A. Telefunken
    Telefunken is a historic German electronics and television brand known for its radios, audio equipment, and consumer electronics.
  • B. Boxtel
    Boxtel is a town and municipality in the southern Netherlands known for its historic center and location between the cities of Eindhoven and ’s-Hertogenbosch.
  • C. Sceptre
    Sceptre is a literary imprint known for publishing high-quality contemporary fiction and non-fiction, often with a focus on distinctive, award-winning voices.
  • D. Philipse
    Philipse is the surname of a prominent colonial-era merchant and landowning family in what is now New York, notably associated with Frederick Philipse I.
  • E. Nokki
    Nokki is one of the four snow owl mascots created to represent the 1998 Winter Olympics held in Nagano, Japan.
  • 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: Fitel
Triple: [Jeff Bezos, employer, Fitel]
Generated description
Fitel was a financial technology startup where Jeff Bezos worked early in his career, before joining D. E. Shaw and later founding Amazon.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fitel
Target entity description: Fitel was a financial technology startup where Jeff Bezos worked early in his career, before joining D. E. Shaw and later founding Amazon.
  • A. Telefunken
    Telefunken is a historic German electronics and television brand known for its radios, audio equipment, and consumer electronics.
  • B. Boxtel
    Boxtel is a town and municipality in the southern Netherlands known for its historic center and location between the cities of Eindhoven and ’s-Hertogenbosch.
  • C. Sceptre
    Sceptre is a literary imprint known for publishing high-quality contemporary fiction and non-fiction, often with a focus on distinctive, award-winning voices.
  • D. Philipse
    Philipse is the surname of a prominent colonial-era merchant and landowning family in what is now New York, notably associated with Frederick Philipse I.
  • E. Nokki
    Nokki is one of the four snow owl mascots created to represent the 1998 Winter Olympics held in Nagano, Japan.
  • 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_69a499171a28819085b993a3ac78e363 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c558e0e081909802753872374d7b completed March 1, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad08c046b08190a448ba2549dc5e00 completed March 8, 2026, 5:27 a.m.
NEDg Description generation batch_69ad09ec3b388190b492e8959a3617c9 completed March 8, 2026, 5:32 a.m.
NED2 Entity disambiguation (via description) batch_69ad0aefb1c88190a368d68454a0b9d0 completed March 8, 2026, 5:36 a.m.
Created at: March 1, 2026, 8 p.m.