Triple
T1487490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neilson |
E29499
|
entity |
| Predicate | hasVariant |
P455
|
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: [Neilson, hasVariant, Nielsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nielsen Context triple: [Neilson, hasVariant, 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.
Bomis
Bomis was an early web portal and search engine company co-founded by Jimmy Wales that later played a key role in funding and incubating Wikipedia.
-
D.
Luminate Data
Luminate Data is a music and entertainment data analytics company that tracks and reports industry metrics such as sales, streaming, and airplay used to compile major charts.
-
E.
NAB
NAB is the commonly used abbreviation for the New American Bible, a Catholic English translation of the Bible widely used in the United States.
- 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_69a498da82e08190ba833330d05f380f |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6a3325881909bbc55efc04ad60f |
completed | March 1, 2026, 11:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad1ca7804c8190b6818ff344908028 |
completed | March 8, 2026, 6:52 a.m. |
Created at: March 1, 2026, 8:12 p.m.