Triple
T9187655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LightWave 3D |
E220498
|
entity |
| Predicate | component |
P35
|
FINISHED |
| Object |
Modeler
Modeler is LightWave 3D’s dedicated 3D modeling application used to create and edit polygonal and subdivision-surface geometry.
|
E784414
|
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: Modeler | Statement: [LightWave 3D, component, Modeler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Modeler Context triple: [LightWave 3D, component, Modeler]
-
A.
Modo
Modo is a Swedish professional ice hockey club known for developing numerous NHL players and competing in the country’s top leagues.
-
B.
Imagineer
An Imagineer is a creative professional at Walt Disney Imagineering who designs and develops Disney theme park attractions, environments, and experiences by blending storytelling, engineering, and art.
-
C.
Modell
Modell is the surname of Art Modell, the influential former owner of the NFL’s Cleveland Browns and Baltimore Ravens.
-
D.
Maquette
Maquette is a first-person recursive puzzle game known for its mind-bending, nested world design and emotional narrative about relationships.
-
E.
Paint 3D
Paint 3D is a modern graphics and 3D modeling application by Microsoft that expands on classic Paint with tools for creating, editing, and sharing both 2D and 3D artwork.
- 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: Modeler Triple: [LightWave 3D, component, Modeler]
Generated description
Modeler is LightWave 3D’s dedicated 3D modeling application used to create and edit polygonal and subdivision-surface geometry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Modeler Target entity description: Modeler is LightWave 3D’s dedicated 3D modeling application used to create and edit polygonal and subdivision-surface geometry.
-
A.
Modo
Modo is a Swedish professional ice hockey club known for developing numerous NHL players and competing in the country’s top leagues.
-
B.
Imagineer
An Imagineer is a creative professional at Walt Disney Imagineering who designs and develops Disney theme park attractions, environments, and experiences by blending storytelling, engineering, and art.
-
C.
Modell
Modell is the surname of Art Modell, the influential former owner of the NFL’s Cleveland Browns and Baltimore Ravens.
-
D.
Maquette
Maquette is a first-person recursive puzzle game known for its mind-bending, nested world design and emotional narrative about relationships.
-
E.
Paint 3D
Paint 3D is a modern graphics and 3D modeling application by Microsoft that expands on classic Paint with tools for creating, editing, and sharing both 2D and 3D artwork.
- 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_69ca83e6d77c81909862b7afef56b1bf |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccc31bd6f88190b2ea644420995e41 |
completed | April 1, 2026, 7:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d05c226bc881909609da0bfbd4748e |
completed | April 4, 2026, 12:32 a.m. |
| NEDg | Description generation | batch_69d060881c908190b22d06eaf9f8b192 |
completed | April 4, 2026, 12:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d0611e76988190be93d1d3dd8f1ab1 |
completed | April 4, 2026, 12:53 a.m. |
Created at: March 30, 2026, 7:24 p.m.