Triple
T16383516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oïl languages |
E397865
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Mayennais
Mayennais is a regional Oïl language variety traditionally spoken in the Mayenne area of western France.
|
E1210225
|
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: Mayennais | Statement: [Oïl languages, hasPart, Mayennais]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mayennais Context triple: [Oïl languages, hasPart, Mayennais]
-
A.
Moulinois
Moulinois is the French term for an inhabitant or native of the town of Moulins in central France.
-
B.
Roannais
Roannais is a natural region in central France known for its rolling countryside, agricultural landscapes, and proximity to the upper Loire River.
-
C.
Mayreau
Mayreau is a small, sparsely populated island in the Grenadines of the Caribbean, known for its tranquil beaches and laid-back village atmosphere.
-
D.
Menez
Menez was a prominent 20th-century Portuguese painter known for her lyrical, introspective style and significant contributions to modern art in Portugal.
-
E.
Nantz
Nantz is the surname of Jim Nantz, a prominent American sportscaster best known for his long-running work with CBS Sports covering events like the NFL, NCAA basketball, and The Masters.
- 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: Mayennais Triple: [Oïl languages, hasPart, Mayennais]
Generated description
Mayennais is a regional Oïl language variety traditionally spoken in the Mayenne area of western France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mayennais Target entity description: Mayennais is a regional Oïl language variety traditionally spoken in the Mayenne area of western France.
-
A.
Moulinois
Moulinois is the French term for an inhabitant or native of the town of Moulins in central France.
-
B.
Roannais
Roannais is a natural region in central France known for its rolling countryside, agricultural landscapes, and proximity to the upper Loire River.
-
C.
Mayreau
Mayreau is a small, sparsely populated island in the Grenadines of the Caribbean, known for its tranquil beaches and laid-back village atmosphere.
-
D.
Menez
Menez was a prominent 20th-century Portuguese painter known for her lyrical, introspective style and significant contributions to modern art in Portugal.
-
E.
Nantz
Nantz is the surname of Jim Nantz, a prominent American sportscaster best known for his long-running work with CBS Sports covering events like the NFL, NCAA basketball, and The Masters.
- 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e319de83248190b5d43646fa9b6cda |
completed | April 18, 2026, 5:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00356b00408190beab51a23011be67 |
completed | May 10, 2026, 7:36 a.m. |
| NEDg | Description generation | batch_6a00369391a08190bb5521e2fcc839c6 |
completed | May 10, 2026, 7:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00374326948190ae039bc689054387 |
completed | May 10, 2026, 7:44 a.m. |
Created at: April 10, 2026, 5:08 a.m.