Triple
T920960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blogger |
E19881
|
entity |
| Predicate | developer |
P73
|
FINISHED |
| Object |
Pyra Labs
Pyra Labs is the software company best known for creating Blogger, one of the earliest and most influential web-based blogging platforms.
|
E107974
|
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: Pyra Labs | Statement: [Blogger, developer, Pyra Labs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pyra Labs Context triple: [Blogger, developer, Pyra Labs]
-
A.
Founders Lab
Founders Lab is an innovation and entrepreneurship space at Elmhurst University that supports student startups and experiential learning in business and technology.
-
B.
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.
-
C.
Habana Labs
Habana Labs is an Israeli-based company specializing in artificial intelligence accelerators and deep learning processors for data centers.
-
D.
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.
-
E.
Zyvex
Zyvex is a pioneering nanotechnology company known for its early work in molecular nanotechnology and advanced manufacturing.
- 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: Pyra Labs Triple: [Blogger, developer, Pyra Labs]
Generated description
Pyra Labs is the software company best known for creating Blogger, one of the earliest and most influential web-based blogging platforms.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pyra Labs Target entity description: Pyra Labs is the software company best known for creating Blogger, one of the earliest and most influential web-based blogging platforms.
-
A.
Founders Lab
Founders Lab is an innovation and entrepreneurship space at Elmhurst University that supports student startups and experiential learning in business and technology.
-
B.
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.
-
C.
Habana Labs
Habana Labs is an Israeli-based company specializing in artificial intelligence accelerators and deep learning processors for data centers.
-
D.
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.
-
E.
Zyvex
Zyvex is a pioneering nanotechnology company known for its early work in molecular nanotechnology and advanced manufacturing.
- 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_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_69a7cf6486d88190b53cd743b08eef33 |
completed | March 4, 2026, 6:21 a.m. |
| NEDg | Description generation | batch_69a7d02d9d308190a9e950ae034b2ec5 |
completed | March 4, 2026, 6:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7d0aac93481908ffc2141d668e9d2 |
completed | March 4, 2026, 6:26 a.m. |
Created at: March 1, 2026, 7:40 p.m.