Triple
T17826812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Collombey-Muraz |
E445138
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Chemex
Chemex is a small village in the municipality of Collombey-Muraz in the canton of Valais, Switzerland.
|
E1289451
|
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: Chemex | Statement: [Collombey-Muraz, hasSettlement, Chemex]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chemex Context triple: [Collombey-Muraz, hasSettlement, Chemex]
-
A.
Melitta
Melitta is a feminine given name of Greek origin, closely related to Melissa and historically associated with meanings like “bee” and “honey.”
-
B.
Keurig
Keurig is a popular American brand best known for its single-serve pod-based coffee makers widely used in homes and offices.
-
C.
French press
The French press is a manual coffee-brewing device that uses a cylindrical carafe, a plunger, and a metal mesh filter to produce a full-bodied, richly flavored coffee.
-
D.
Tassimo
Tassimo is a single-serve hot beverage system brand known for its coffee and other drink pods, originally developed and marketed by Kraft Foods.
-
E.
Faema
Faema was a prominent professional Italian cycling team of the 1950s and 1960s, best known for sponsoring and supporting legendary riders such as Eddy Merckx.
- 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: Chemex Triple: [Collombey-Muraz, hasSettlement, Chemex]
Generated description
Chemex is a small village in the municipality of Collombey-Muraz in the canton of Valais, Switzerland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chemex Target entity description: Chemex is a small village in the municipality of Collombey-Muraz in the canton of Valais, Switzerland.
-
A.
Melitta
Melitta is a feminine given name of Greek origin, closely related to Melissa and historically associated with meanings like “bee” and “honey.”
-
B.
Keurig
Keurig is a popular American brand best known for its single-serve pod-based coffee makers widely used in homes and offices.
-
C.
French press
The French press is a manual coffee-brewing device that uses a cylindrical carafe, a plunger, and a metal mesh filter to produce a full-bodied, richly flavored coffee.
-
D.
Tassimo
Tassimo is a single-serve hot beverage system brand known for its coffee and other drink pods, originally developed and marketed by Kraft Foods.
-
E.
Faema
Faema was a prominent professional Italian cycling team of the 1950s and 1960s, best known for sponsoring and supporting legendary riders such as Eddy Merckx.
- 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_69d8b9f0de78819099395b14db75a8a6 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48914e20481908883d1da194f446c |
completed | April 19, 2026, 7:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a02ff6d07308190bcf6c959204f89a6 |
completed | May 12, 2026, 10:22 a.m. |
| NEDg | Description generation | batch_6a03003084fc8190b7272f7d2e0735d7 |
completed | May 12, 2026, 10:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0300e885e481909c76dfbac2fd1009 |
completed | May 12, 2026, 10:28 a.m. |
Created at: April 10, 2026, 10:15 a.m.