Triple
T7117269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wirecutter, Inc. |
E165850
|
entity |
| Predicate | founder |
P104
|
FINISHED |
| Object | Brian Lam |
E642207
|
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: Brian Lam | Statement: [Wirecutter, Inc., founder, Brian Lam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brian Lam Context triple: [Wirecutter, Inc., founder, Brian Lam]
-
A.
Brian Lam
chosen
Brian Lam is a technology journalist and entrepreneur best known for founding the product review site Wirecutter and previously serving as an editor at Gizmodo.
-
B.
Ian Bannen
Ian Bannen was a Scottish character actor known for his versatile performances in film, television, and theatre, including acclaimed roles in movies such as "The Flight of the Phoenix" and "Braveheart."
-
C.
Graeme Ferguson
Graeme Ferguson was a Canadian filmmaker and co-founder of the IMAX large-format cinema technology.
-
D.
Neil Cuthbert
Neil Cuthbert is an American screenwriter and actor best known for co-writing the cult Halloween film "Hocus Pocus" and working on several other fantasy and comedy movies.
-
E.
Fraser Sampson
Fraser Sampson is a British lawyer and public official known for his leadership roles overseeing police conduct, biometrics, and surveillance camera regulation in the UK.
- 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_69c6888227bc8190a1394679e3116f90 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e617a528819085d4b8e1b5699966 |
completed | March 27, 2026, 8:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7ad86ac688190af97b42d0cb36b84 |
completed | March 28, 2026, 10:29 a.m. |
Created at: March 27, 2026, 2:43 p.m.