Triple
T16959718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gronings |
E411393
|
entity |
| Predicate | hasEndonym |
P1435
|
FINISHED |
| Object |
Grunnegs
Grunnegs is the local endonym for the Gronings dialect of Low Saxon spoken in the Dutch province of Groningen and surrounding areas.
|
E1243681
|
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: Grunnegs | Statement: [Gronings, hasEndonym, Grunnegs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grunnegs Context triple: [Gronings, hasEndonym, Grunnegs]
-
A.
Gruden
Gruden is a surname most prominently associated with Jon Gruden, a former NFL head coach and television analyst.
-
B.
Grong
Grong is a rural municipality in Trøndelag county, central Norway, known for its forests, rivers, and role as a regional transport and service center in the Namdalen district.
-
C.
Grødem
Grødem is a coastal village in Randaberg municipality in Rogaland county, Norway, known for its residential areas and proximity to the city of Stavanger.
-
D.
Drongen
Drongen is a district of the Belgian city of Ghent, known as a suburban area in East Flanders.
-
E.
Frogn
Frogn is a coastal municipality in Viken county, Norway, known for the historic Oscarsborg Fortress in the Oslofjord.
- 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: Grunnegs Triple: [Gronings, hasEndonym, Grunnegs]
Generated description
Grunnegs is the local endonym for the Gronings dialect of Low Saxon spoken in the Dutch province of Groningen and surrounding areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Grunnegs Target entity description: Grunnegs is the local endonym for the Gronings dialect of Low Saxon spoken in the Dutch province of Groningen and surrounding areas.
-
A.
Gruden
Gruden is a surname most prominently associated with Jon Gruden, a former NFL head coach and television analyst.
-
B.
Grong
Grong is a rural municipality in Trøndelag county, central Norway, known for its forests, rivers, and role as a regional transport and service center in the Namdalen district.
-
C.
Grødem
Grødem is a coastal village in Randaberg municipality in Rogaland county, Norway, known for its residential areas and proximity to the city of Stavanger.
-
D.
Drongen
Drongen is a district of the Belgian city of Ghent, known as a suburban area in East Flanders.
-
E.
Frogn
Frogn is a coastal municipality in Viken county, Norway, known for the historic Oscarsborg Fortress in the Oslofjord.
- 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_69d886c9c9d481909afe222093641cae |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d01f9ba881908dc8820b92869a63 |
completed | April 18, 2026, 6:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d468f5048190aa43b212ec7a7306 |
completed | May 10, 2026, 6:54 p.m. |
| NEDg | Description generation | batch_6a00d5f5f0448190be407979539fcd80 |
completed | May 10, 2026, 7:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00d6e1add481908cce9048e3746e7c |
completed | May 10, 2026, 7:05 p.m. |
Created at: April 10, 2026, 5:31 a.m.