Triple
T18204134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hugging Face |
E435862
|
entity |
| Predicate | notableProduct |
P1448
|
FINISHED |
| Object |
Spaces
Spaces is Hugging Face’s platform for hosting and sharing interactive machine learning demos and applications directly in the browser.
|
E1312402
|
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: Spaces | Statement: [Hugging Face, notableProduct, Spaces]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Spaces Context triple: [Hugging Face, notableProduct, Spaces]
-
A.
Spaces
Spaces is a virtual desktop feature in macOS that lets users organize and switch between multiple workspaces to manage open applications and windows more efficiently.
-
B.
Espacio
"Espacio" is a hip-hop track by Black Rob that showcases his gritty lyrical style over a dark, atmospheric beat.
-
C.
The Space
The Space is an intimate London fringe theatre and arts venue known for showcasing innovative and emerging performance work.
-
D.
Space
Space is a Canadian specialty television channel known for broadcasting science fiction, fantasy, horror, and genre-related programming.
-
E.
Space
Space is JetBrains’ integrated team collaboration and development platform that combines source code hosting, project management, communication tools, and CI/CD in a single environment.
- 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: Spaces Triple: [Hugging Face, notableProduct, Spaces]
Generated description
Spaces is Hugging Face’s platform for hosting and sharing interactive machine learning demos and applications directly in the browser.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Spaces Target entity description: Spaces is Hugging Face’s platform for hosting and sharing interactive machine learning demos and applications directly in the browser.
-
A.
Spaces
Spaces is a virtual desktop feature in macOS that lets users organize and switch between multiple workspaces to manage open applications and windows more efficiently.
-
B.
Espacio
"Espacio" is a hip-hop track by Black Rob that showcases his gritty lyrical style over a dark, atmospheric beat.
-
C.
The Space
The Space is an intimate London fringe theatre and arts venue known for showcasing innovative and emerging performance work.
-
D.
Space
Space is a Canadian specialty television channel known for broadcasting science fiction, fantasy, horror, and genre-related programming.
-
E.
Space
Space is JetBrains’ integrated team collaboration and development platform that combines source code hosting, project management, communication tools, and CI/CD in a single environment.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e221bbbc819088a7559a46b7d4e7 |
completed | April 19, 2026, 2:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a039f0e52108190913cc5c667619d89 |
completed | May 12, 2026, 9:43 p.m. |
| NEDg | Description generation | batch_6a039fdd9c4c819083b450657d0ece43 |
completed | May 12, 2026, 9:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03a0d6de8c8190b1f94c7de0856143 |
completed | May 12, 2026, 9:51 p.m. |
Created at: April 10, 2026, 10:32 a.m.