Triple
T18520058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Designated Market Area |
E452560
|
entity |
| Predicate | definedBy |
P773
|
FINISHED |
| Object | Nielsen |
—
|
NE NERFINISHED |
How this triple was built (2 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: Nielsen | Statement: [Designated Market Area, definedBy, Nielsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nielsen Context triple: [Designated Market Area, definedBy, Nielsen]
-
A.
Nielsen
Nielsen is a common Scandinavian surname, particularly prevalent in Denmark and Norway, traditionally meaning "son of Niels."
-
B.
Nielson
Nielson is a surname and given name that functions as a spelling variant of Nelson, commonly of Scandinavian or English origin.
-
C.
Nielsen Company
chosen
Nielsen Company is a global measurement and data analytics firm best known for providing audience and consumer insights across media, entertainment, and retail industries.
-
D.
Kantar (historically)
Kantar is a major global data, insights, and consulting company that was historically owned by the advertising and communications group WPP plc.
-
E.
Gallup
Gallup is a small city in northwestern New Mexico known as a historic stop along Route 66 and a cultural center for Native American art and trading.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d386df84819092355ebb260d848e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5338ce7e481908ee69ffe4f30d5a4 |
completed | April 19, 2026, 7:57 p.m. |
Created at: April 10, 2026, 11:37 a.m.