Triple
T9187290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pegasos II |
E220490
|
entity |
| Predicate | marketedBy |
P4613
|
FINISHED |
| Object |
Genesi Sarl
Genesi Sarl is a computer hardware company best known for developing and distributing the Pegasos line of PowerPC-based motherboards and systems.
|
E784392
|
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: Genesi Sarl | Statement: [Pegasos II, marketedBy, Genesi Sarl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Genesi Sarl Context triple: [Pegasos II, marketedBy, Genesi Sarl]
-
A.
Lyria SAS
Lyria SAS is a Franco-Swiss rail company that operates high-speed TGV Lyria train services connecting France and Switzerland.
-
B.
Regenesis Group
Regenesis Group is a sustainability-focused organization known for advancing green building and regenerative development practices.
-
C.
Vinci SA
Vinci SA is a major French multinational concessions and construction company specializing in infrastructure development and management worldwide.
-
D.
Iliad SA
Iliad SA is a French telecommunications company best known for its low-cost mobile and internet services, including the Free brand.
-
E.
Egis Group
Egis Group is a global engineering and infrastructure consulting firm that manages and operates transportation facilities such as airports, roads, and urban transit systems.
- 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: Genesi Sarl Triple: [Pegasos II, marketedBy, Genesi Sarl]
Generated description
Genesi Sarl is a computer hardware company best known for developing and distributing the Pegasos line of PowerPC-based motherboards and systems.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Genesi Sarl Target entity description: Genesi Sarl is a computer hardware company best known for developing and distributing the Pegasos line of PowerPC-based motherboards and systems.
-
A.
Lyria SAS
Lyria SAS is a Franco-Swiss rail company that operates high-speed TGV Lyria train services connecting France and Switzerland.
-
B.
Regenesis Group
Regenesis Group is a sustainability-focused organization known for advancing green building and regenerative development practices.
-
C.
Vinci SA
Vinci SA is a major French multinational concessions and construction company specializing in infrastructure development and management worldwide.
-
D.
Iliad SA
Iliad SA is a French telecommunications company best known for its low-cost mobile and internet services, including the Free brand.
-
E.
Egis Group
Egis Group is a global engineering and infrastructure consulting firm that manages and operates transportation facilities such as airports, roads, and urban transit systems.
- 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.