Triple
T6711061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erik Nielsen |
E153141
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Nielsen |
E25294
|
NE FINISHED |
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: [Erik Nielsen, familyName, Nielsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nielsen Context triple: [Erik Nielsen, familyName, Nielsen]
-
A.
Nielsen
chosen
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
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.
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.
-
E.
Gallup
Gallup is a global analytics and advisory company best known for its public opinion polls and research on politics, economics, and well-being.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c68808d8d8819087369015270788fe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d107380481909cc761dc182834c1 |
completed | March 27, 2026, 6:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c700906a9c81908a121db4291195d8 |
completed | March 27, 2026, 10:11 p.m. |
Created at: March 27, 2026, 2:06 p.m.