Triple
T6559150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Nelson |
E152530
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Matthew Nelson |
E68520
|
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: Matthew Nelson | Statement: [David Nelson, child, Matthew Nelson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthew Nelson Context triple: [David Nelson, child, Matthew Nelson]
-
A.
Matthew Nelson
chosen
Matthew Nelson is an American musician best known as one half of the twin brother rock duo Nelson and as a son of rock and roll star Ricky Nelson.
-
B.
Matthew Stuecken
Matthew Stuecken is a film screenwriter best known for co-writing the psychological sci-fi thriller "10 Cloverfield Lane."
-
C.
Matthew Jensen
Matthew Jensen is a cinematographer best known for his work on major films such as the 2017 superhero movie "Wonder Woman."
-
D.
Jack Nelson
Jack Nelson was an early 20th-century American actor known for his roles in silent films.
-
E.
Matthew McNulty
Matthew McNulty is a British actor known for his work in film and television, including roles in series like "Misfits," "The Mill," and "Versailles."
- 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_69c688058d6881908c19b309cc55dbfa |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ae202e508190a08a0c0584648b83 |
completed | March 27, 2026, 4:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70ae438b0819086449c169e5c7e49 |
completed | March 27, 2026, 10:55 p.m. |
Created at: March 27, 2026, 1:52 p.m.