Triple
T7878681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amway |
E182922
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object |
Glister
Glister is an oral care brand from Amway known for its toothpaste and related dental hygiene products.
|
E701096
|
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: Glister | Statement: [Amway, brand, Glister]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Glister Context triple: [Amway, brand, Glister]
-
A.
Dragonseye
Dragonseye is a science fantasy novel in Anne McCaffrey’s Dragonriders of Pern series that explores the early days of dragonrider society as it prepares for the deadly return of Thread.
-
B.
The Crystal
The Crystal is a landmark sustainable building and exhibition center in London known for its distinctive glass architecture and focus on urban sustainability and green technologies.
-
C.
Golden Vale
Golden Vale is a fertile, pastoral region in southwestern Ireland renowned for its rich farmland and dairy production.
-
D.
Fonte das Lágrimas
Fonte das Lágrimas is a historic fountain in Coimbra, Portugal, romantically associated with the tragic medieval love story of Pedro and Inês de Castro.
-
E.
Silvermine
Silvermine is a scenic conservation area within Cape Town’s Table Mountain National Park, known for its fynbos-covered slopes, hiking trails, and reservoirs.
- 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: Glister Triple: [Amway, brand, Glister]
Generated description
Glister is an oral care brand from Amway known for its toothpaste and related dental hygiene products.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Glister Target entity description: Glister is an oral care brand from Amway known for its toothpaste and related dental hygiene products.
-
A.
Dragonseye
Dragonseye is a science fantasy novel in Anne McCaffrey’s Dragonriders of Pern series that explores the early days of dragonrider society as it prepares for the deadly return of Thread.
-
B.
The Crystal
The Crystal is a landmark sustainable building and exhibition center in London known for its distinctive glass architecture and focus on urban sustainability and green technologies.
-
C.
Golden Vale
Golden Vale is a fertile, pastoral region in southwestern Ireland renowned for its rich farmland and dairy production.
-
D.
Fonte das Lágrimas
Fonte das Lágrimas is a historic fountain in Coimbra, Portugal, romantically associated with the tragic medieval love story of Pedro and Inês de Castro.
-
E.
Silvermine
Silvermine is a scenic conservation area within Cape Town’s Table Mountain National Park, known for its fynbos-covered slopes, hiking trails, and reservoirs.
- 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_69ca828a17248190b46defe758bc5ad3 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39bd64e481909f699e7dd2818b8f |
completed | March 31, 2026, 3:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5b86c20081909aa029cda7c48d44 |
completed | March 31, 2026, 5:28 a.m. |
| NEDg | Description generation | batch_69cb7631d10881908e3c7dacb98520cd |
completed | March 31, 2026, 7:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cbbf847f3c819092d690d8d65f6d60 |
completed | March 31, 2026, 12:35 p.m. |
Created at: March 30, 2026, 4:57 p.m.