Triple

T920966
Position Surface form Disambiguated ID Type / Status
Subject Blogger E19881 entity
Predicate originalDeveloper P184 FINISHED
Object Pyra Labs E107974 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: Pyra Labs | Statement: [Blogger, originalDeveloper, Pyra Labs]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pyra Labs
Context triple: [Blogger, originalDeveloper, Pyra Labs]
  • A. Pyra Labs chosen
    Pyra Labs is the software company best known for creating Blogger, one of the earliest and most influential web-based blogging platforms.
  • B. Founders Lab
    Founders Lab is an innovation and entrepreneurship space at Elmhurst University that supports student startups and experiential learning in business and technology.
  • C. Sugar Labs
    Sugar Labs is a nonprofit organization that develops and maintains the Sugar learning platform, an open-source educational software environment originally created for the One Laptop per Child project.
  • D. Habana Labs
    Habana Labs is an Israeli-based company specializing in artificial intelligence accelerators and deep learning processors for data centers.
  • E. Cadabra, Inc.
    Cadabra, Inc. was the original name of the company that later became Amazon, the multinational e-commerce and technology giant founded by Jeff Bezos.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a493a099788190a696d9d8408cbaf4 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3120dbc81908362158fe3ffa889 completed March 1, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7ee094c94819093578c949db7ded9 completed March 4, 2026, 8:32 a.m.
Created at: March 1, 2026, 7:40 p.m.